1 HOK comparison of CASAL and Casal2 model configurations

This document compares the results of at least 2 CASAL model configurations (base and at least one sensitivity) and up to 8 Casal2 model configurations (3 BetaDiff, 2 CppAD, and 3 ADOL-C).

The CASAL model sensitivity 1 has a smaller minimisation tolerance value than the CASAL base model (1e-9 vs. 1e-6).

The Casal2 ADOL-C and BetaDiff low tolerance models have a smaller tolerance value than the CASAL base model (1e-9 vs. 1e-6). The Casal2 CppAD models have a tolerance value of 1e-9.

1.1 HOK model characteristics

The main characteristics of the Test Case HOK (hoki) CASAL model are:

  • one stock, ages 1 - 17
  • one area, although many characteristics are separated into “east” and “west”
  • years 1972 - 2018, projection years 2019 - 2023
  • five time steps: Oct_Nov, Dec_Mar, Apr_Jun, End_Jun, and Jul_Sep
  • five stock categories: west.sa, east.cr, west.cr, west.wc, and east.cs (labeled “stock.area”)
  • five migration processes, which have age-specific proportions specified
  • sex-specific natural mortality-at-age is double exponential
  • area-specific von Bertalanffy age-length relationship
  • area-specific length-weight relationship (\(W = aL^b\))
  • area-specific Beverton-Holt stock-recruitment relationships, with steepness (h) 0.75
  • ageing error is specified
  • surveys with double normal selectivity
  • six area-specific fisheries with double normal selectivity

Observation data include:

  • survey indices
  • survey proportions-at-age
  • fishery proportions-at-age

Parameters estimated include:

  • area-specific B0
  • parameters for the natural mortality-at-age ogive
  • catchability (q) for the surveys
  • parameters for the selectivity curves for the surveys
  • parameters for the selectivity curves for the fisheries
  • migration proportions by age
  • area-specific YCS (recruitment deviations)

1.2 R environment

## [1] "Fri May 28 10:29:01 2021"
## R version 3.6.0 (2019-04-26)
## Platform: x86_64-redhat-linux-gnu (64-bit)
## Running under: CentOS Linux 7 (Core)
## 
## Matrix products: default
## BLAS/LAPACK: /usr/lib64/R/lib/libRblas.so
## 
## locale:
##  [1] LC_CTYPE=en_NZ.UTF-8       LC_NUMERIC=C              
##  [3] LC_TIME=en_NZ.UTF-8        LC_COLLATE=en_NZ.UTF-8    
##  [5] LC_MONETARY=en_NZ.UTF-8    LC_MESSAGES=en_NZ.UTF-8   
##  [7] LC_PAPER=en_GB.UTF_8       LC_NAME=C                 
##  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
## [11] LC_MEASUREMENT=en_NZ.UTF-8 LC_IDENTIFICATION=C       
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
##  [1] casal2_1.0     casal_2.30     devtools_2.4.1 usethis_2.0.1  rlist_0.4.6.1 
##  [6] ggthemes_4.2.4 gridExtra_2.3  coda_0.19-4    ggmcmc_1.5.1.1 ggplot2_3.3.3 
## [11] tidyr_1.1.3    dplyr_1.0.6   
## 
## loaded via a namespace (and not attached):
##  [1] Rcpp_1.0.6         lattice_0.20-44    prettyunits_1.1.1  ps_1.6.0          
##  [5] assertthat_0.2.1   rprojroot_2.0.2    digest_0.6.27      utf8_1.2.1        
##  [9] R6_2.5.0           plyr_1.8.6         evaluate_0.14      pillar_1.6.1      
## [13] rlang_0.4.11       data.table_1.14.0  callr_3.7.0        jquerylib_0.1.4   
## [17] rmarkdown_2.8      desc_1.3.0         stringr_1.4.0      munsell_0.5.0     
## [21] compiler_3.6.0     xfun_0.23          pkgconfig_2.0.3    pkgbuild_1.2.0    
## [25] htmltools_0.5.1.1  tidyselect_1.1.1   tibble_3.1.2       reshape_0.8.8     
## [29] fansi_0.4.2        crayon_1.4.1       withr_2.4.2        grid_3.6.0        
## [33] jsonlite_1.7.2     GGally_2.1.1       gtable_0.3.0       lifecycle_1.0.0   
## [37] DBI_1.1.1          magrittr_2.0.1     scales_1.1.1       cli_2.5.0         
## [41] stringi_1.6.2      cachem_1.0.5       fs_1.5.0           remotes_2.3.0     
## [45] testthat_3.0.2     bslib_0.2.5.1      ellipsis_0.3.2     generics_0.1.0    
## [49] vctrs_0.3.8        RColorBrewer_1.1-2 tools_3.6.0        glue_1.4.2        
## [53] purrr_0.3.4        processx_3.5.2     pkgload_1.2.1      fastmap_1.1.0     
## [57] yaml_2.2.1         colorspace_1.4-1   sessioninfo_1.1.1  memoise_2.0.0     
## [61] knitr_1.33         sass_0.4.0

1.3 CASAL and Casal2 model output

source('../../R-functions/report_read_in_CASAL_MPD_files.R')
source('../../R-functions/report_read_in_Casal2_MPD_files.R')

1.4 Tables

Tables of parameter estimates and objective function components for the CASAL and Casal2 model MPD results

CASAL parameter estimates
rownamesBase_ModelSensitivity_1Percent_Diff
q[CSacous].q               0.431200.431200.000
q[WCacous].q               0.300300.300200.033
q[CRsum].q               0.074310.074310.000
q[SAsum].q               0.059250.059250.000
q[SAaut].q               0.067170.067170.000
relative_abundance[CRsumbio].cv_process_error0.140500.140500.000
relative_abundance[SAsumbio].cv_process_error0.430600.430600.000
log_B0_total                 14.3400014.340000.000
B0_prop_stock1                 0.328700.328700.000
natural_mortality.all             0.296000.296000.000
selectivity[Wspsl].shift_a         -0.21740-0.217400.000
recruitment[E].YCS1            0.447800.447800.000
recruitment[E].YCS2            0.726800.726800.000
recruitment[E].YCS3            0.784500.784500.000
recruitment[E].YCS4            1.360001.360000.000
recruitment[E].YCS5            0.987700.98780-0.010
recruitment[E].YCS6            0.329300.329300.000
recruitment[E].YCS7            0.447200.447200.000
recruitment[E].YCS8            0.265600.265600.000
recruitment[E].YCS9            0.434200.434200.000
recruitment[E].YCS10           0.488000.488000.000
recruitment[E].YCS11           0.395700.395700.000
recruitment[E].YCS12           0.217900.217900.000
recruitment[E].YCS13           1.036001.036000.000
recruitment[E].YCS14           0.958900.958900.000
recruitment[E].YCS15           0.429000.429000.000
recruitment[E].YCS16           0.138100.138100.000
recruitment[E].YCS17           0.375000.375000.000
recruitment[E].YCS18           0.391700.391600.026
recruitment[E].YCS19           0.383100.383100.000
recruitment[E].YCS20           0.562900.562900.000
recruitment[E].YCS21           0.264000.264000.000
recruitment[E].YCS22           0.284500.284500.000
recruitment[E].YCS23           0.450000.450000.000
recruitment[E].YCS24           0.253100.253100.000
recruitment[E].YCS25           0.060000.060000.000
recruitment[E].YCS26           0.462200.462200.000
recruitment[E].YCS27           0.161600.161600.000
recruitment[E].YCS28           0.266900.266900.000
recruitment[E].YCS29           0.500400.500400.000
recruitment[E].YCS30           0.520000.520000.000
recruitment[E].YCS31           0.508800.508800.000
recruitment[E].YCS32           0.600600.600600.000
recruitment[E].YCS33           0.522100.522100.000
recruitment[E].YCS34           0.373000.373000.000
recruitment[E].YCS35           0.526800.526800.000
recruitment[E].YCS36           0.158600.158600.000
recruitment[E].YCS37           0.660600.660600.000
recruitment[E].YCS38           0.156000.156000.000
recruitment[E].YCS39           0.185800.185800.000
recruitment[E].YCS40           0.730600.730600.000
recruitment[E].YCS41           0.739100.739000.014
recruitment[E].YCS42           1.195001.195000.000
recruitment[W].YCS1            0.457000.457000.000
recruitment[W].YCS2            0.822200.822200.000
recruitment[W].YCS3            0.670000.670000.000
recruitment[W].YCS4            0.653900.653900.000
recruitment[W].YCS5            0.465900.465900.000
recruitment[W].YCS6            0.515100.515100.000
recruitment[W].YCS7            0.578200.578200.000
recruitment[W].YCS8            0.473300.473300.000
recruitment[W].YCS9            0.871900.871900.000
recruitment[W].YCS10           0.836400.83650-0.012
recruitment[W].YCS11           0.320200.320200.000
recruitment[W].YCS12           0.165000.165000.000
recruitment[W].YCS13           1.476001.476000.000
recruitment[W].YCS14           0.772700.77280-0.013
recruitment[W].YCS15           0.081350.081350.000
recruitment[W].YCS16           0.081580.081580.000
recruitment[W].YCS17           0.892800.892800.000
recruitment[W].YCS18           1.268001.268000.000
recruitment[W].YCS19           0.377200.377200.000
recruitment[W].YCS20           0.959400.959400.000
recruitment[W].YCS21           0.221100.221100.000
recruitment[W].YCS22           0.197200.197200.000
recruitment[W].YCS23           0.237900.23800-0.042
recruitment[W].YCS24           0.202900.202900.000
recruitment[W].YCS25           0.060000.060000.000
recruitment[W].YCS26           0.373000.373000.000
recruitment[W].YCS27           0.095480.095480.000
recruitment[W].YCS28           0.795600.795600.000
recruitment[W].YCS29           0.465200.465200.000
recruitment[W].YCS30           0.516600.516600.000
recruitment[W].YCS31           0.511300.511300.000
recruitment[W].YCS32           0.755400.755400.000
recruitment[W].YCS33           0.638900.638900.000
recruitment[W].YCS34           0.616900.616900.000
recruitment[W].YCS35           0.578400.578400.000
recruitment[W].YCS36           0.145500.145500.000
recruitment[W].YCS37           0.974800.974800.000
recruitment[W].YCS38           0.160200.160200.000
recruitment[W].YCS39           0.244400.244400.000
recruitment[W].YCS40           2.197002.197000.000
recruitment[W].YCS41           2.152002.152000.000
recruitment[W].YCS42           1.195001.195000.000
migration[Whome].rates_all1      0.327800.327800.000
migration[Whome].rates_all2      0.307800.307800.000
migration[Whome].rates_all3      0.476200.476200.000
migration[Whome].rates_all4      0.141800.141800.000
migration[Whome].rates_all5      0.468500.468400.021
migration[Whome].rates_all6      0.749800.75030-0.067
migration[Whome].rates_all7      0.794700.788400.793
migration[Whome].rates_all8      1.000001.000000.000
migration[Espmg].rates_all1      0.005660.005660.000
migration[Espmg].rates_all2      0.160200.160200.000
migration[Espmg].rates_all3      0.324100.324100.000
migration[Espmg].rates_all4      0.431200.431200.000
migration[Espmg].rates_all5      0.385500.385500.000
migration[Espmg].rates_all6      0.465400.465300.021
migration[Espmg].rates_all7      0.599000.599000.000
migration[Espmg].rates_all8      0.607800.607800.000
migration[Wspmg].rates_all1      0.106100.106100.000
migration[Wspmg].rates_all2      0.287700.287700.000
migration[Wspmg].rates_all3      0.270800.270800.000
migration[Wspmg].rates_all4      0.455300.455300.000
migration[Wspmg].rates_all5      0.484700.484700.000
migration[Wspmg].rates_all6      0.527100.527100.000
migration[Wspmg].rates_all7      0.660600.660600.000
migration[Wspmg].rates_all8      0.596300.596300.000
selectivity[Enspsl].all1            3.567003.567000.000
selectivity[Enspsl].all2            1.221001.221000.000
selectivity[Enspsl].all3            15.7100015.710000.000
selectivity[Wnspsl].all1            5.341005.341000.000
selectivity[Wnspsl].all2            2.839002.839000.000
selectivity[Wnspsl].all3            13.3800013.380000.000
selectivity[Espsl].all1            10.8800010.880000.000
selectivity[Espsl].all2            11.6800011.680000.000
selectivity[Espsl].all3            3.982003.982000.000
selectivity[CRsl].all1            1.000001.000000.000
selectivity[CRsl].all2            1.000001.000000.000
selectivity[CRsl].all3            9.300009.300000.000
selectivity[SAsl].all1            14.2500014.250000.000
selectivity[SAsl].all2            8.755008.75600-0.011
selectivity[SAsl].all3            1.315001.315000.000
Casal2 parameter estimates
rownamesbetadiff_casal_flags_onbetadiff_casal_flags_offbetadiff_casal_flags_on_low_tolcppad_casal_flags_oncppad_casal_flags_offadolc_casal_flags_onadolc_casal_flags_offadolc_casal_flags_on_low_tol
catchability[CSacous].q               0.427240.427860.431160.434200.434200.427240.427240.42786
catchability[WCacous].q               0.312840.312440.300240.297040.297040.312840.312840.31244
catchability[CRsum].q               0.068320.068110.074310.075990.075990.068320.068320.06811
catchability[SAsum].q               0.067170.067060.059250.056030.056030.067170.067170.06706
catchability[SAaut].q               0.075780.075630.067170.063510.063510.075780.075780.07563
observation[CRsumbio].process_error   0.140940.140890.140480.140180.140180.140940.140940.14089
observation[SAsumbio].process_error   0.423640.423810.430610.430920.430920.423640.423640.42381
process[recruit_E].b0              548394.00000547497.00000555125.00000554646.00000554646.00000548395.00000548396.00000547497.00000
process[recruit_W].b0              1082670.000001083360.000001133680.000001147420.000001147420.000001082670.000001082670.000001083360.00000
process[Instant_mortality].m{west.sa}             0.312710.312930.295980.291790.291790.312710.312710.31293
time_varying[shifted_mu].a               -0.22921-0.22959-0.21744-0.21691-0.21691-0.22921-0.22921-0.22959
process[recruit_E].ycs_values{1975}0.445380.445890.447820.447450.447450.445370.445380.44589
process[recruit_E].ycs_values{1976}0.729380.730520.726800.724230.724230.729390.729390.73052
process[recruit_E].ycs_values{1977}0.792310.793320.784540.780920.780920.792310.792310.79332
process[recruit_E].ycs_values{1978}1.386441.388271.360011.350411.350411.386441.386451.38827
process[recruit_E].ycs_values{1979}1.002651.003720.987760.982030.982031.002651.002651.00372
process[recruit_E].ycs_values{1980}0.334370.334620.329320.327610.327610.334370.334370.33462
process[recruit_E].ycs_values{1981}0.455020.455350.447230.444720.444720.455020.455020.45535
process[recruit_E].ycs_values{1982}0.269740.269890.265560.264280.264280.269740.269740.26989
process[recruit_E].ycs_values{1983}0.441060.441000.434180.432120.432120.441060.441060.44100
process[recruit_E].ycs_values{1984}0.494120.494220.488040.486130.486130.494120.494120.49422
process[recruit_E].ycs_values{1985}0.400100.400140.395700.394360.394360.400100.400100.40014
process[recruit_E].ycs_values{1986}0.219780.219820.217910.217360.217360.219780.219780.21982
process[recruit_E].ycs_values{1987}1.041311.040951.036401.034391.034391.041311.041311.04095
process[recruit_E].ycs_values{1988}0.963460.963150.958910.957570.957570.963460.963460.96315
process[recruit_E].ycs_values{1989}0.430950.431120.428990.428640.428640.430950.430950.43112
process[recruit_E].ycs_values{1990}0.137970.137980.138100.138170.138170.137970.137970.13798
process[recruit_E].ycs_values{1991}0.373850.373350.375000.375130.375130.373850.373850.37335
process[recruit_E].ycs_values{1992}0.388580.387570.391640.392540.392540.388580.388580.38757
process[recruit_E].ycs_values{1993}0.379950.379880.383100.384080.384080.379950.379950.37988
process[recruit_E].ycs_values{1994}0.557940.557260.562850.564420.564420.557940.557940.55726
process[recruit_E].ycs_values{1995}0.261780.261780.263990.264730.264730.261780.261780.26178
process[recruit_E].ycs_values{1996}0.282510.282480.284470.285180.285180.282510.282510.28248
process[recruit_E].ycs_values{1997}0.447810.447590.450030.451070.451070.447810.447810.44759
process[recruit_E].ycs_values{1998}0.252640.252490.253070.253460.253460.252640.252640.25249
process[recruit_E].ycs_values{1999}0.060000.060000.060000.060000.060000.060000.060000.06000
process[recruit_E].ycs_values{2000}0.460130.459870.462200.463120.463120.460130.460130.45987
process[recruit_E].ycs_values{2001}0.160860.160870.161650.161930.161930.160860.160860.16087
process[recruit_E].ycs_values{2002}0.266110.265600.266890.267180.267180.266110.266110.26560
process[recruit_E].ycs_values{2003}0.499590.499430.500380.500870.500870.499590.499590.49943
process[recruit_E].ycs_values{2004}0.520530.520310.520030.520210.520210.520530.520530.52031
process[recruit_E].ycs_values{2005}0.507640.507540.508820.509360.509360.507640.507640.50754
process[recruit_E].ycs_values{2006}0.600130.599860.600550.600980.600980.600130.600130.59986
process[recruit_E].ycs_values{2007}0.520870.520800.522150.522690.522690.520870.520870.52080
process[recruit_E].ycs_values{2008}0.371150.370470.373000.373650.373650.371150.371150.37047
process[recruit_E].ycs_values{2009}0.527900.527860.526810.527000.527000.527900.527900.52786
process[recruit_E].ycs_values{2010}0.156950.156900.158640.159120.159120.156950.156950.15690
process[recruit_E].ycs_values{2011}0.660470.660290.660580.661400.661400.660470.660470.66029
process[recruit_E].ycs_values{2012}0.155540.155580.156000.156270.156270.155540.155540.15558
process[recruit_E].ycs_values{2013}0.185180.185180.185840.186190.186190.185180.185180.18518
process[recruit_E].ycs_values{2014}0.728450.728090.730620.731810.731810.728440.728440.72808
process[recruit_E].ycs_values{2015}0.755870.752310.739000.734820.734820.755860.755870.75231
process[recruit_E].ycs_values{2016}1.188861.189391.195151.195481.195481.188861.188861.18939
process[recruit_W].ycs_values{1975}0.458690.458720.457020.453780.453780.458690.458690.45872
process[recruit_W].ycs_values{1976}0.814220.814330.822180.837250.837250.814220.814220.81433
process[recruit_W].ycs_values{1977}0.685140.684940.670000.677420.677420.685150.685150.68494
process[recruit_W].ycs_values{1978}0.669370.669050.653900.652200.652200.669370.669370.66905
process[recruit_W].ycs_values{1979}0.473080.472760.465900.465240.465240.473070.473070.47276
process[recruit_W].ycs_values{1980}0.520640.520520.515120.514470.514470.520640.520640.52052
process[recruit_W].ycs_values{1981}0.583440.583280.578240.576690.576690.583440.583440.58328
process[recruit_W].ycs_values{1982}0.474620.474400.473280.472740.472740.474620.474620.47440
process[recruit_W].ycs_values{1983}0.873090.873750.871920.870830.870830.873090.873090.87375
process[recruit_W].ycs_values{1984}0.836330.837380.836460.834500.834500.836330.836330.83738
process[recruit_W].ycs_values{1985}0.319420.319750.320240.319740.319740.319420.319420.31975
process[recruit_W].ycs_values{1986}0.164930.164840.164970.165080.165080.164930.164930.16484
process[recruit_W].ycs_values{1987}1.480071.480661.475551.478261.478261.480071.480071.48066
process[recruit_W].ycs_values{1988}0.774540.775300.772760.774300.774300.774540.774540.77530
process[recruit_W].ycs_values{1989}0.081480.081470.081340.081380.081380.081480.081480.08147
process[recruit_W].ycs_values{1990}0.081830.081800.081580.081500.081500.081830.081830.08180
process[recruit_W].ycs_values{1991}0.891970.891890.892800.894490.894490.891970.891980.89189
process[recruit_W].ycs_values{1992}1.267571.267831.267781.266841.266841.267571.267581.26783
process[recruit_W].ycs_values{1993}0.376520.376480.377220.376920.376920.376520.376520.37648
process[recruit_W].ycs_values{1994}0.955790.955570.959390.959680.959680.955790.955790.95557
process[recruit_W].ycs_values{1995}0.220260.220150.221130.221080.221080.220260.220270.22015
process[recruit_W].ycs_values{1996}0.196320.196260.197180.196960.196960.196320.196320.19626
process[recruit_W].ycs_values{1997}0.236430.236780.237950.237660.237660.236430.236430.23678
process[recruit_W].ycs_values{1998}0.200410.200610.202920.203060.203060.200410.200410.20061
process[recruit_W].ycs_values{1999}0.060000.060000.060000.060000.060000.060000.060000.06000
process[recruit_W].ycs_values{2000}0.370890.371330.373040.372930.372930.370890.370890.37133
process[recruit_W].ycs_values{2001}0.095060.095100.095480.095490.095490.095060.095060.09510
process[recruit_W].ycs_values{2002}0.795530.795760.795580.794800.794800.795530.795530.79576
process[recruit_W].ycs_values{2003}0.465700.465880.465170.464520.464520.465700.465700.46588
process[recruit_W].ycs_values{2004}0.517610.517840.516620.515860.515860.517610.517610.51784
process[recruit_W].ycs_values{2005}0.513050.513140.511260.510350.510350.513050.513050.51314
process[recruit_W].ycs_values{2006}0.754750.754870.755440.754940.754940.754750.754750.75487
process[recruit_W].ycs_values{2007}0.636920.636760.638910.638870.638870.636920.636920.63676
process[recruit_W].ycs_values{2008}0.615640.616140.616860.616620.616620.615640.615640.61614
process[recruit_W].ycs_values{2009}0.573050.572920.578410.579300.579300.573050.573050.57292
process[recruit_W].ycs_values{2010}0.146180.146260.145470.145230.145230.146180.146180.14626
process[recruit_W].ycs_values{2011}0.967080.966690.974780.975560.975560.967080.967080.96669
process[recruit_W].ycs_values{2012}0.159090.158970.160160.160260.160260.159090.159090.15897
process[recruit_W].ycs_values{2013}0.244020.243890.244440.244500.244500.244020.244020.24389
process[recruit_W].ycs_values{2014}2.186512.184742.196572.198622.198622.186512.186512.18474
process[recruit_W].ycs_values{2015}2.147582.149692.152042.154082.154082.147582.147582.14969
process[recruit_W].ycs_values{2016}1.189091.189621.195391.195721.195721.189091.189091.18962
selectivity[sel_Whome].v{1}            0.321930.321360.327830.330950.330950.321930.321930.32136
selectivity[sel_Whome].v{2}            0.284920.283860.307780.314200.314200.284910.284920.28386
selectivity[sel_Whome].v{3}            0.459720.457750.476200.477010.477010.459720.459720.45775
selectivity[sel_Whome].v{4}            0.135490.135020.141840.139310.139310.135490.135490.13502
selectivity[sel_Whome].v{5}            0.437820.431690.468360.475670.475670.437820.437820.43169
selectivity[sel_Whome].v{6}            0.708210.718910.750260.748040.748040.708210.708210.71891
selectivity[sel_Whome].v{7}            0.999880.759600.788410.736410.736410.999890.999880.75961
selectivity[sel_Espmg].v{1}            0.005640.005640.005660.005630.005630.005640.005640.00564
selectivity[sel_Espmg].v{2}            0.159120.159010.160210.159790.159790.159120.159120.15901
selectivity[sel_Espmg].v{3}            0.320820.320560.324110.323760.323760.320820.320820.32056
selectivity[sel_Espmg].v{4}            0.425470.425130.431230.431310.431310.425470.425470.42513
selectivity[sel_Espmg].v{5}            0.379530.379270.385460.385890.385890.379530.379530.37927
selectivity[sel_Espmg].v{6}            0.458760.458470.465350.465900.465900.458760.458760.45847
selectivity[sel_Espmg].v{7}            0.590810.590440.599020.599690.599690.590810.590810.59044
selectivity[sel_Espmg].v{8}            0.611000.610640.607780.606350.606350.611000.611000.61064
selectivity[sel_Wspmg].v{1}            0.105560.105530.106140.105460.105460.105560.105560.10553
selectivity[sel_Wspmg].v{2}            0.291360.291390.287740.285540.285540.291360.291360.29139
selectivity[sel_Wspmg].v{3}            0.270680.270660.270760.270810.270810.270680.270680.27066
selectivity[sel_Wspmg].v{4}            0.455270.455200.455250.455730.455730.455270.455270.45520
selectivity[sel_Wspmg].v{5}            0.484210.484340.484660.485200.485200.484210.484210.48434
selectivity[sel_Wspmg].v{6}            0.524960.523980.527110.528270.528270.524960.524960.52398
selectivity[sel_Wspmg].v{7}            0.652980.655910.660620.662640.662640.652980.652980.65591
selectivity[sel_Wspmg].v{8}            0.601530.601010.596270.594000.594000.601530.601530.60101
selectivity[Enspsl].mu              3.573183.572273.567163.557403.557403.573183.573183.57227
selectivity[Enspsl].sigma_l         1.222451.222061.221081.217121.217121.222451.222451.22206
selectivity[Enspsl].sigma_r         50.0000050.0000015.7137014.6268014.6268050.0000049.9999050.00000
selectivity[Wnspsl].mu              5.328395.329525.341175.320475.320475.328405.328405.32952
selectivity[Wnspsl].sigma_l         2.778152.778462.839342.832592.832592.778152.778162.77846
selectivity[Wnspsl].sigma_r         49.9997049.9992013.3789012.3922012.3922049.9999049.9999049.99980
selectivity[Espsl].mu              11.2567011.2547010.8788010.7912010.7912011.2567011.2567011.25470
selectivity[Espsl].sigma_l         10.8674010.8594011.6775011.9773011.9773010.8674010.8674010.85940
selectivity[Espsl].sigma_r         4.026254.029123.981653.977473.977474.026254.026254.02912
selectivity[CRsl].mu              1.000001.000001.000001.000001.000001.000001.000001.00000
selectivity[CRsl].sigma_l         46.5222046.5220046.0218025.5000025.5000046.5221046.5219046.52200
selectivity[CRsl].sigma_r         10.0929010.087809.300429.128009.1280010.0928010.0929010.08780
selectivity[SAsl].mu              14.8685014.8648014.2523013.4844013.4844014.8685014.8685014.86480
selectivity[SAsl].sigma_l         8.694698.692818.755588.370058.370058.694688.694678.69281
selectivity[SAsl].sigma_r         1.000001.000001.315191.859021.859021.000001.000001.00000
Casal2 parameter estimates: Percent Difference from betadiff_casal_flags_on
rownamesbetadiff_casal_flags_onbetadiff_casal_flags_offbetadiff_casal_flags_on_low_tolcppad_casal_flags_oncppad_casal_flags_offadolc_casal_flags_onadolc_casal_flags_offadolc_casal_flags_on_low_tol
catchability[CSacous].q               0.000-0.145-0.918-1.628-1.6280.0000.000-0.145
catchability[WCacous].q               0.0000.1284.0285.0525.0520.0000.0000.128
catchability[CRsum].q               0.0000.298-8.765-11.232-11.2320.0000.0000.298
catchability[SAsum].q               0.0000.17211.79716.58816.5880.0000.0000.172
catchability[SAaut].q               0.0000.18811.36316.18816.1880.0000.0000.188
observation[CRsumbio].process_error   0.0000.0350.3280.5400.5400.0000.0000.035
observation[SAsumbio].process_error   0.000-0.040-1.645-1.718-1.7180.000-0.000-0.040
process[recruit_E].b0              0.0000.164-1.227-1.140-1.140-0.000-0.0000.164
process[recruit_W].b0              0.000-0.064-4.712-5.981-5.9810.0000.000-0.064
process[Instant_mortality].m{west.sa}             0.000-0.0705.3496.6916.6910.0000.000-0.070
time_varying[shifted_mu].a               0.000-0.1665.1355.3695.3690.0000.000-0.166
process[recruit_E].ycs_values{1975}0.000-0.116-0.548-0.466-0.4660.000-0.000-0.117
process[recruit_E].ycs_values{1976}0.000-0.1560.3540.7070.707-0.001-0.001-0.157
process[recruit_E].ycs_values{1977}0.000-0.1280.9811.4381.4380.0000.000-0.127
process[recruit_E].ycs_values{1978}0.000-0.1321.9062.5992.5990.000-0.001-0.132
process[recruit_E].ycs_values{1979}0.000-0.1071.4852.0572.0570.0000.000-0.107
process[recruit_E].ycs_values{1980}0.000-0.0741.5112.0222.022-0.000-0.001-0.074
process[recruit_E].ycs_values{1981}0.000-0.0721.7122.2622.262-0.000-0.000-0.072
process[recruit_E].ycs_values{1982}0.000-0.0551.5512.0282.0280.0000.000-0.055
process[recruit_E].ycs_values{1983}0.0000.0121.5592.0272.027-0.000-0.0000.012
process[recruit_E].ycs_values{1984}0.000-0.0221.2291.6161.616-0.000-0.000-0.022
process[recruit_E].ycs_values{1985}0.000-0.0091.1011.4351.435-0.000-0.000-0.009
process[recruit_E].ycs_values{1986}0.000-0.0220.8501.1021.1020.000-0.000-0.022
process[recruit_E].ycs_values{1987}0.0000.0350.4720.6650.6650.0000.0000.035
process[recruit_E].ycs_values{1988}0.0000.0320.4710.6110.6110.0000.0000.032
process[recruit_E].ycs_values{1989}0.000-0.0400.4550.5360.5360.000-0.000-0.040
process[recruit_E].ycs_values{1990}0.000-0.009-0.101-0.149-0.1490.0000.000-0.009
process[recruit_E].ycs_values{1991}0.0000.135-0.307-0.341-0.3410.0000.0000.135
process[recruit_E].ycs_values{1992}0.0000.260-0.787-1.019-1.0190.0000.0000.260
process[recruit_E].ycs_values{1993}0.0000.016-0.831-1.087-1.0870.0000.0000.016
process[recruit_E].ycs_values{1994}0.0000.123-0.880-1.160-1.1600.000-0.0000.122
process[recruit_E].ycs_values{1995}0.000-0.002-0.843-1.128-1.1280.0000.000-0.002
process[recruit_E].ycs_values{1996}0.0000.008-0.695-0.944-0.9440.000-0.0000.008
process[recruit_E].ycs_values{1997}0.0000.049-0.496-0.729-0.7290.0000.0000.049
process[recruit_E].ycs_values{1998}0.0000.061-0.170-0.323-0.3230.000-0.0000.061
process[recruit_E].ycs_values{1999}0.0000.0000.0000.0000.0000.0000.0000.000
process[recruit_E].ycs_values{2000}0.0000.057-0.449-0.650-0.6500.0000.0000.057
process[recruit_E].ycs_values{2001}0.000-0.007-0.489-0.663-0.6630.0000.000-0.007
process[recruit_E].ycs_values{2002}0.0000.191-0.294-0.402-0.4020.0000.0000.191
process[recruit_E].ycs_values{2003}0.0000.031-0.159-0.256-0.2560.0000.0000.031
process[recruit_E].ycs_values{2004}0.0000.0430.0960.0610.0610.000-0.0000.043
process[recruit_E].ycs_values{2005}0.0000.021-0.233-0.337-0.3370.0000.0000.021
process[recruit_E].ycs_values{2006}0.0000.046-0.070-0.141-0.1410.0000.0000.046
process[recruit_E].ycs_values{2007}0.0000.014-0.245-0.349-0.3490.0000.0000.014
process[recruit_E].ycs_values{2008}0.0000.184-0.500-0.674-0.6740.0000.0000.184
process[recruit_E].ycs_values{2009}0.0000.0070.2060.1700.1700.0000.0000.007
process[recruit_E].ycs_values{2010}0.0000.032-1.074-1.384-1.3840.000-0.0010.032
process[recruit_E].ycs_values{2011}0.0000.028-0.017-0.140-0.1400.0000.0000.028
process[recruit_E].ycs_values{2012}0.000-0.030-0.293-0.470-0.4700.0000.001-0.030
process[recruit_E].ycs_values{2013}0.0000.002-0.355-0.545-0.5450.000-0.0010.002
process[recruit_E].ycs_values{2014}0.0000.049-0.299-0.461-0.4610.0000.0000.050
process[recruit_E].ycs_values{2015}0.0000.4712.2322.7852.7850.0010.0000.471
process[recruit_E].ycs_values{2016}0.000-0.045-0.529-0.557-0.5570.0000.000-0.045
process[recruit_W].ycs_values{1975}0.000-0.0060.3651.0711.0710.0000.001-0.005
process[recruit_W].ycs_values{1976}0.000-0.014-0.977-2.828-2.8280.0000.000-0.014
process[recruit_W].ycs_values{1977}0.0000.0302.2101.1281.128-0.000-0.0010.030
process[recruit_W].ycs_values{1978}0.0000.0472.3112.5662.5660.0000.0000.047
process[recruit_W].ycs_values{1979}0.0000.0671.5181.6561.6560.0000.0000.067
process[recruit_W].ycs_values{1980}0.0000.0231.0611.1861.1860.0000.0000.023
process[recruit_W].ycs_values{1981}0.0000.0270.8921.1571.1570.0000.0000.027
process[recruit_W].ycs_values{1982}0.0000.0470.2840.3970.3970.0000.0000.047
process[recruit_W].ycs_values{1983}0.000-0.0760.1340.2590.2590.0000.000-0.076
process[recruit_W].ycs_values{1984}0.000-0.125-0.0160.2190.2190.0000.000-0.125
process[recruit_W].ycs_values{1985}0.000-0.103-0.257-0.099-0.0990.0000.000-0.103
process[recruit_W].ycs_values{1986}0.0000.055-0.021-0.087-0.0870.0010.0000.055
process[recruit_W].ycs_values{1987}0.000-0.0400.3050.1220.1220.0000.000-0.040
process[recruit_W].ycs_values{1988}0.000-0.0990.2290.0300.0300.0000.000-0.098
process[recruit_W].ycs_values{1989}0.0000.0030.1600.1220.122-0.000-0.0000.003
process[recruit_W].ycs_values{1990}0.0000.0370.3040.3960.3960.0000.0000.037
process[recruit_W].ycs_values{1991}0.0000.009-0.093-0.282-0.2820.000-0.0000.009
process[recruit_W].ycs_values{1992}0.000-0.021-0.0170.0580.0580.000-0.001-0.021
process[recruit_W].ycs_values{1993}0.0000.011-0.185-0.106-0.1060.000-0.0000.011
process[recruit_W].ycs_values{1994}0.0000.023-0.377-0.407-0.4070.000-0.0000.023
process[recruit_W].ycs_values{1995}0.0000.054-0.392-0.371-0.3710.000-0.0000.054
process[recruit_W].ycs_values{1996}0.0000.028-0.440-0.330-0.3300.0000.0000.028
process[recruit_W].ycs_values{1997}0.000-0.147-0.643-0.521-0.5210.000-0.000-0.147
process[recruit_W].ycs_values{1998}0.000-0.099-1.251-1.324-1.3240.0000.000-0.099
process[recruit_W].ycs_values{1999}0.0000.0000.0000.0000.0000.0000.0000.000
process[recruit_W].ycs_values{2000}0.000-0.117-0.580-0.551-0.5510.0000.000-0.117
process[recruit_W].ycs_values{2001}0.000-0.037-0.446-0.454-0.4540.0000.000-0.037
process[recruit_W].ycs_values{2002}0.000-0.029-0.0070.0920.0920.0000.000-0.029
process[recruit_W].ycs_values{2003}0.000-0.0390.1140.2550.2550.0000.000-0.039
process[recruit_W].ycs_values{2004}0.000-0.0450.1910.3380.3380.0000.000-0.044
process[recruit_W].ycs_values{2005}0.000-0.0170.3490.5260.526-0.000-0.000-0.017
process[recruit_W].ycs_values{2006}0.000-0.015-0.091-0.024-0.0240.0000.000-0.015
process[recruit_W].ycs_values{2007}0.0000.026-0.312-0.306-0.3060.0000.0000.026
process[recruit_W].ycs_values{2008}0.000-0.080-0.198-0.159-0.1590.0000.000-0.080
process[recruit_W].ycs_values{2009}0.0000.024-0.934-1.090-1.0900.0000.0000.024
process[recruit_W].ycs_values{2010}0.000-0.0560.4820.6460.646-0.001-0.001-0.056
process[recruit_W].ycs_values{2011}0.0000.041-0.796-0.877-0.8770.0000.0000.041
process[recruit_W].ycs_values{2012}0.0000.075-0.674-0.733-0.7330.0000.0000.075
process[recruit_W].ycs_values{2013}0.0000.052-0.172-0.198-0.1980.0000.0000.052
process[recruit_W].ycs_values{2014}0.0000.081-0.460-0.554-0.5540.0000.0000.081
process[recruit_W].ycs_values{2015}0.000-0.098-0.208-0.303-0.3030.0000.000-0.098
process[recruit_W].ycs_values{2016}0.000-0.045-0.530-0.558-0.5580.0000.000-0.045
selectivity[sel_Whome].v{1}            0.0000.177-1.833-2.801-2.8010.0000.0000.177
selectivity[sel_Whome].v{2}            0.0000.370-8.027-10.276-10.2760.0000.0000.370
selectivity[sel_Whome].v{3}            0.0000.429-3.584-3.761-3.7610.0000.0000.430
selectivity[sel_Whome].v{4}            0.0000.343-4.687-2.821-2.8210.000-0.0010.343
selectivity[sel_Whome].v{5}            0.0001.400-6.975-8.645-8.6450.0000.0001.400
selectivity[sel_Whome].v{6}            0.000-1.510-5.938-5.624-5.624-0.000-0.000-1.510
selectivity[sel_Whome].v{7}            0.00024.03021.14926.35026.350-0.001-0.00124.030
selectivity[sel_Espmg].v{1}            0.0000.080-0.3320.0930.093-0.0000.0000.080
selectivity[sel_Espmg].v{2}            0.0000.073-0.683-0.418-0.4180.0000.0000.073
selectivity[sel_Espmg].v{3}            0.0000.078-1.028-0.918-0.9180.0000.0000.078
selectivity[sel_Espmg].v{4}            0.0000.079-1.354-1.374-1.3740.0000.0000.079
selectivity[sel_Espmg].v{5}            0.0000.069-1.563-1.676-1.6760.0000.0000.069
selectivity[sel_Espmg].v{6}            0.0000.063-1.436-1.556-1.5560.0000.0000.063
selectivity[sel_Espmg].v{7}            0.0000.062-1.389-1.503-1.5030.000-0.0000.062
selectivity[sel_Espmg].v{8}            0.0000.0600.5280.7620.7620.0000.0000.060
selectivity[sel_Wspmg].v{1}            0.0000.033-0.5520.0990.0990.0000.0010.033
selectivity[sel_Wspmg].v{2}            0.000-0.0101.2421.9981.9980.0000.000-0.010
selectivity[sel_Wspmg].v{3}            0.0000.008-0.029-0.048-0.0480.0000.0000.008
selectivity[sel_Wspmg].v{4}            0.0000.0170.004-0.101-0.1010.0000.0000.017
selectivity[sel_Wspmg].v{5}            0.000-0.026-0.092-0.205-0.205-0.000-0.000-0.026
selectivity[sel_Wspmg].v{6}            0.0000.187-0.409-0.631-0.6310.0000.0000.187
selectivity[sel_Wspmg].v{7}            0.000-0.449-1.170-1.479-1.4790.0000.000-0.449
selectivity[sel_Wspmg].v{8}            0.0000.0870.8751.2531.2530.0000.0000.087
selectivity[Enspsl].mu              0.0000.0250.1680.4420.4420.0000.0000.025
selectivity[Enspsl].sigma_l         0.0000.0320.1120.4360.4360.0000.0000.032
selectivity[Enspsl].sigma_r         0.0000.00068.57370.74670.7460.0000.0000.000
selectivity[Wnspsl].mu              0.000-0.021-0.2400.1490.149-0.000-0.000-0.021
selectivity[Wnspsl].sigma_l         0.000-0.011-2.203-1.960-1.9600.000-0.000-0.011
selectivity[Wnspsl].sigma_r         0.0000.00173.24275.21575.215-0.000-0.000-0.000
selectivity[Espsl].mu              0.0000.0183.3574.1354.1350.0000.0000.018
selectivity[Espsl].sigma_l         0.0000.074-7.454-10.213-10.2130.0000.0000.074
selectivity[Espsl].sigma_r         0.000-0.0711.1081.2121.2120.0000.000-0.071
selectivity[CRsl].mu              0.0000.0000.0000.0000.0000.0000.0000.000
selectivity[CRsl].sigma_l         0.0000.0001.07645.18745.1870.0000.0010.000
selectivity[CRsl].sigma_r         0.0000.0517.8529.5609.5600.0010.0000.051
selectivity[SAsl].mu              0.0000.0254.1449.3099.3090.0000.0000.025
selectivity[SAsl].sigma_l         0.0000.022-0.7003.7343.7340.0000.0000.022
selectivity[SAsl].sigma_r         0.0000.000-31.519-85.902-85.9020.0000.0000.000

CASAL objective function component values
ComponentBase_ModelSensitivity_1
CRsumbio-31.030-31.030
CSacous-9.835-9.836
SAautbio-3.984-3.984
SAsumbio-6.146-6.146
WCacous-5.916-5.916
CRsumage323.800323.800
SAautage35.12035.120
SAsumage221.100221.100
EnspOLF24.28024.280
Enspage256.100256.100
Espage581.500581.500
WnspOLF70.25070.250
Wnspage157.000157.000
Wspage364.800364.800
pspawn-13.130-13.130
pspawn_1993-6.015-6.015
prior_on_q[CSacous].q-0.839-0.839
prior_on_q[WCacous].q-1.202-1.202
prior_on_q[CRsum].q-2.207-2.207
prior_on_q[SAsum].q-1.557-1.557
prior_on_q[SAaut].q-1.762-1.762
prior_on_relative_abundance[CRsumbio].cv_process_error0.0000.000
prior_on_relative_abundance[SAsumbio].cv_process_error0.0000.000
prior_on_log_B0_total0.0000.000
prior_on_B0_prop_stock112.56012.560
prior_on_natural_mortality.all-1.217-1.217
prior_on_selectivity[Wspsl].shift_a0.3780.378
prior_on_recruitment[E].YCS-13.750-13.750
prior_on_recruitment[W].YCS-1.785-1.785
prior_on_migration[Whome].rates_all0.0000.000
prior_on_migration[Espmg].rates_all0.0000.000
prior_on_migration[Wspmg].rates_all0.0000.000
prior_on_selectivity[Enspsl].all0.0000.000
prior_on_selectivity[Wnspsl].all0.0000.000
prior_on_selectivity[Espsl].all0.0000.000
prior_on_selectivity[CRsl].all0.0000.000
prior_on_selectivity[SAsl].all0.0000.000
Umax_Ensp10.0000.000
Umax_Ensp20.0000.000
Umax_Wnsp10.0000.000
Umax_Wnsp20.0000.000
Umax_Esp0.0000.000
Umax_Wsp0.0000.000
YCS.eq.160.0000.000
sp.migr0.0130.013
Total1947.0001947.000
Casal2 objective function component values
rownamesbetadiff_casal_flags_onbetadiff_casal_flags_offbetadiff_casal_flags_on_low_tolcppad_casal_flags_oncppad_casal_flags_offadolc_casal_flags_onadolc_casal_flags_offadolc_casal_flags_on_low_tol
observation->CSacous-1991                 2.3422.3442.4042.4172.4172.3422.3422.344
observation->CSacous-1993                 -0.577-0.577-0.588-0.591-0.591-0.577-0.577-0.577
observation->CSacous-1994                 -0.016-0.016-0.030-0.034-0.034-0.016-0.016-0.016
observation->CSacous-1995                 -0.562-0.562-0.567-0.568-0.568-0.562-0.562-0.562
observation->CSacous-1996                 -0.026-0.0270.0130.0220.022-0.026-0.027-0.027
observation->CSacous-1997                 -0.912-0.912-0.899-0.895-0.895-0.912-0.912-0.912
observation->CSacous-1998                 -0.054-0.055-0.0040.0080.008-0.054-0.054-0.055
observation->CSacous-1999                 -1.025-1.025-1.012-1.009-1.009-1.025-1.025-1.025
observation->CSacous-2001                 -1.217-1.217-1.211-1.210-1.210-1.217-1.217-1.217
observation->CSacous-2002                 -0.297-0.297-0.338-0.349-0.349-0.297-0.297-0.297
observation->CSacous-2003                 -0.845-0.845-0.863-0.868-0.868-0.845-0.845-0.845
observation->CSacous-2005                 -0.929-0.929-0.927-0.927-0.927-0.929-0.929-0.929
observation->CSacous-2006                 -0.939-0.939-0.950-0.953-0.953-0.939-0.939-0.939
observation->CSacous-2007                 -0.623-0.623-0.600-0.593-0.593-0.623-0.623-0.623
observation->CSacous-2008                 -1.094-1.094-1.125-1.133-1.133-1.094-1.094-1.094
observation->CSacous-2009                 -0.185-0.186-0.110-0.089-0.089-0.185-0.185-0.186
observation->CSacous-2011                 -1.021-1.021-1.000-0.995-0.995-1.021-1.021-1.021
observation->CSacous-2013                 -0.892-0.892-0.855-0.846-0.846-0.892-0.892-0.892
observation->CSacous-2015                 -0.190-0.191-0.150-0.142-0.142-0.190-0.190-0.191
observation->CSacous-2017                 -1.020-1.020-1.021-1.021-1.021-1.020-1.020-1.020
observation->WCacous-1988                 -0.588-0.588-0.588-0.589-0.589-0.588-0.588-0.588
observation->WCacous-1989                 -0.183-0.184-0.168-0.159-0.159-0.183-0.183-0.184
observation->WCacous-1990                 -0.332-0.331-0.327-0.323-0.323-0.332-0.332-0.331
observation->WCacous-1991                 -0.425-0.425-0.425-0.425-0.425-0.425-0.425-0.425
observation->WCacous-1992                 -0.744-0.744-0.744-0.744-0.744-0.744-0.744-0.744
observation->WCacous-1993                 -0.369-0.371-0.374-0.380-0.380-0.369-0.369-0.371
observation->WCacous-1997                 -0.054-0.055-0.043-0.041-0.041-0.054-0.054-0.055
observation->WCacous-2000                 -1.265-1.264-1.272-1.273-1.273-1.265-1.265-1.264
observation->WCacous-2012                 -0.906-0.906-0.896-0.889-0.889-0.906-0.906-0.906
observation->WCacous-2013                 -1.079-1.079-1.079-1.078-1.078-1.079-1.079-1.079
observation->CRsumbio-1992                 -1.634-1.634-1.647-1.650-1.650-1.634-1.634-1.634
observation->CRsumbio-1993                 0.0400.0410.0430.0330.0330.0400.0400.041
observation->CRsumbio-1994                 -1.760-1.761-1.760-1.760-1.760-1.760-1.760-1.761
observation->CRsumbio-1995                 -1.425-1.431-1.406-1.403-1.403-1.425-1.425-1.431
observation->CRsumbio-1996                 -1.690-1.691-1.699-1.701-1.701-1.690-1.690-1.691
observation->CRsumbio-1997                 -0.607-0.609-0.635-0.642-0.642-0.607-0.607-0.609
observation->CRsumbio-1998                 -1.203-1.205-1.210-1.211-1.211-1.203-1.203-1.205
observation->CRsumbio-1999                 -0.953-0.950-0.919-0.914-0.914-0.953-0.953-0.950
observation->CRsumbio-2000                 -1.629-1.629-1.632-1.633-1.633-1.629-1.629-1.629
observation->CRsumbio-2001                 -1.773-1.773-1.775-1.776-1.776-1.773-1.773-1.773
observation->CRsumbio-2002                 -1.209-1.205-1.206-1.206-1.206-1.209-1.209-1.205
observation->CRsumbio-2003                 -1.749-1.748-1.744-1.744-1.744-1.749-1.749-1.748
observation->CRsumbio-2004                 -0.818-0.821-0.803-0.802-0.802-0.818-0.818-0.821
observation->CRsumbio-2005                 -1.471-1.470-1.477-1.477-1.477-1.471-1.471-1.470
observation->CRsumbio-2006                 -1.314-1.314-1.306-1.299-1.299-1.314-1.314-1.314
observation->CRsumbio-2007                 -0.727-0.726-0.756-0.767-0.767-0.727-0.727-0.726
observation->CRsumbio-2008                 -0.373-0.376-0.402-0.409-0.409-0.373-0.373-0.376
observation->CRsumbio-2009                 -0.586-0.587-0.559-0.547-0.547-0.586-0.586-0.587
observation->CRsumbio-2010                 -1.349-1.350-1.359-1.362-1.362-1.349-1.349-1.350
observation->CRsumbio-2011                 -1.096-1.094-1.105-1.109-1.109-1.096-1.096-1.094
observation->CRsumbio-2012                 -1.439-1.438-1.448-1.451-1.451-1.439-1.439-1.438
observation->CRsumbio-2013                 -1.494-1.494-1.491-1.490-1.490-1.494-1.494-1.494
observation->CRsumbio-2014                 -1.768-1.768-1.770-1.772-1.772-1.768-1.768-1.768
observation->CRsumbio-2016                 -1.410-1.411-1.411-1.414-1.414-1.410-1.410-1.411
observation->CRsumbio-2018                 -1.552-1.552-1.554-1.556-1.556-1.552-1.552-1.552
observation->SAsumbio-1992                 -0.597-0.596-0.588-0.593-0.593-0.597-0.597-0.596
observation->SAsumbio-1993                 -0.314-0.314-0.309-0.319-0.319-0.314-0.314-0.314
observation->SAsumbio-1994                 0.1960.1940.1860.1660.1660.1960.1960.194
observation->SAsumbio-2001                 -0.835-0.834-0.822-0.825-0.825-0.835-0.835-0.834
observation->SAsumbio-2002                 -0.794-0.794-0.777-0.774-0.774-0.794-0.794-0.794
observation->SAsumbio-2003                 -0.837-0.836-0.825-0.822-0.822-0.837-0.837-0.836
observation->SAsumbio-2004                 0.7320.7350.7340.7390.7390.7320.7320.735
observation->SAsumbio-2005                 -0.258-0.255-0.218-0.201-0.201-0.258-0.258-0.255
observation->SAsumbio-2006                 -0.600-0.598-0.558-0.553-0.553-0.600-0.600-0.598
observation->SAsumbio-2007                 0.6360.6370.6540.6260.6260.6360.6360.637
observation->SAsumbio-2008                 -0.461-0.463-0.462-0.449-0.449-0.461-0.461-0.463
observation->SAsumbio-2009                 -0.585-0.584-0.583-0.583-0.583-0.585-0.585-0.584
observation->SAsumbio-2010                 -0.143-0.146-0.147-0.147-0.147-0.143-0.143-0.146
observation->SAsumbio-2012                 -0.848-0.848-0.835-0.834-0.834-0.848-0.848-0.848
observation->SAsumbio-2013                 -0.797-0.796-0.786-0.789-0.789-0.797-0.797-0.796
observation->SAsumbio-2015                 -0.200-0.201-0.189-0.175-0.175-0.200-0.200-0.201
observation->SAsumbio-2017                 -0.638-0.638-0.620-0.616-0.616-0.638-0.638-0.638
observation->SAautbio-1992                 -1.459-1.460-1.450-1.445-1.445-1.459-1.459-1.460
observation->SAautbio-1996                 -1.233-1.232-1.250-1.260-1.260-1.233-1.233-1.232
observation->SAautbio-1998                 -1.308-1.306-1.284-1.275-1.275-1.308-1.308-1.306
observation->Espage-1988                 19.79319.79019.64019.60819.60819.79319.79319.790
observation->Espage-1989                 15.85815.85715.86215.86415.86415.85815.85815.857
observation->Espage-1990                 21.48821.48621.44621.43521.43521.48821.48821.486
observation->Espage-1991                 20.64120.64020.61220.60520.60520.64120.64120.640
observation->Espage-1992                 24.08924.09224.02024.00824.00824.08924.08924.092
observation->Espage-1993                 19.30519.30419.32819.33419.33419.30519.30519.304
observation->Espage-1994                 20.52820.52220.50320.49720.49720.52820.52820.522
observation->Espage-1995                 22.54122.53022.55922.56322.56322.54122.54122.530
observation->Espage-1996                 18.59018.59018.57718.57418.57418.59018.59018.590
observation->Espage-1997                 20.97420.97820.96420.96620.96620.97420.97420.978
observation->Espage-1998                 20.58720.57920.61120.61420.61420.58720.58720.579
observation->Espage-1999                 22.88622.87522.86222.85422.85422.88622.88622.875
observation->Espage-2000                 23.32123.32123.31423.30723.30723.32123.32123.321
observation->Espage-2001                 20.73520.73520.77320.77820.77820.73520.73520.735
observation->Espage-2002                 26.24826.24326.28726.29726.29726.24826.24826.243
observation->Espage-2003                 19.12019.11819.12019.11819.11819.12019.12019.118
observation->Espage-2004                 22.69222.69822.64222.63822.63822.69222.69222.698
observation->Espage-2005                 26.12226.12026.07026.06826.06826.12226.12226.120
observation->Espage-2006                 23.24223.24523.14923.13023.13023.24223.24223.245
observation->Espage-2007                 25.27425.27725.21025.20425.20425.27425.27425.277
observation->Espage-2008                 22.16722.16622.12922.12422.12422.16722.16822.166
observation->Espage-2009                 18.69118.69118.69018.69118.69118.69118.69118.691
observation->Espage-2010                 21.85521.85621.85121.85221.85221.85521.85521.856
observation->Espage-2014                 20.61620.61420.64820.65720.65720.61620.61620.614
observation->Espage-2015                 21.82321.82021.87021.87721.87721.82321.82321.820
observation->Espage-2016                 21.20421.20321.20421.20421.20421.20421.20421.203
observation->Espage-2017                 21.57521.57821.56321.56121.56121.57521.57521.578
observation->Wspage-1988                 15.72415.72915.75315.71615.71615.72415.72415.729
observation->Wspage-1989                 11.55511.55811.56611.55811.55811.55511.55511.558
observation->Wspage-1990                 11.75211.75011.79011.80411.80411.75211.75211.750
observation->Wspage-1991                 13.03613.03713.05113.07013.07013.03613.03613.037
observation->Wspage-1992                 10.17810.17910.17010.17310.17310.17810.17810.179
observation->Wspage-1993                 10.56910.57110.57910.57710.57710.56910.56910.571
observation->Wspage-1994                 9.9189.9189.9249.9239.9239.9189.9189.918
observation->Wspage-1995                 13.40313.39913.39613.39313.39313.40313.40313.399
observation->Wspage-1996                 11.84011.84111.84411.84811.84811.84011.84011.841
observation->Wspage-1997                 11.23011.23311.24311.24911.24911.23011.23011.233
observation->Wspage-1998                 11.76111.76111.76211.76411.76411.76111.76111.761
observation->Wspage-1999                 11.97511.97611.98111.98611.98611.97511.97511.976
observation->Wspage-2000                 11.25611.25611.26011.26311.26311.25611.25611.256
observation->Wspage-2001                 12.17912.18112.20112.20812.20812.17912.17912.181
observation->Wspage-2002                 9.7319.7329.7459.7509.7509.7319.7319.732
observation->Wspage-2003                 9.5559.5559.5569.5579.5579.5559.5559.555
observation->Wspage-2004                 14.34014.34214.30414.29414.29414.34014.34014.342
observation->Wspage-2005                 14.93214.93414.97714.98514.98514.93214.93214.934
observation->Wspage-2006                 13.81713.81713.87213.87913.87913.81713.81713.817
observation->Wspage-2007                 11.49811.50011.51611.51711.51711.49811.49811.500
observation->Wspage-2008                 12.19512.19612.19412.19312.19312.19512.19512.196
observation->Wspage-2009                 12.63112.63512.59412.58712.58712.63112.63112.635
observation->Wspage-2010                 11.31611.31711.29911.29511.29511.31611.31611.317
observation->Wspage-2011                 11.15411.15511.13711.13111.13111.15411.15411.155
observation->Wspage-2012                 11.86711.86611.86011.86011.86011.86711.86711.866
observation->Wspage-2013                 11.04111.04311.06511.07111.07111.04111.04111.043
observation->Wspage-2014                 12.94412.94412.94112.94112.94112.94412.94412.944
observation->Wspage-2015                 13.13413.13613.10113.09213.09213.13413.13413.136
observation->Wspage-2016                 14.27214.26814.27314.27614.27614.27214.27214.268
observation->Wspage-2017                 13.74513.74613.79713.81313.81313.74513.74513.746
observation->EnspOLF-1992                 4.3974.3964.3884.3924.3924.3974.3974.396
observation->EnspOLF-1994                 6.6476.6456.6786.6756.6756.6476.6476.645
observation->EnspOLF-1996                 7.8977.8997.9067.9137.9137.8977.8977.899
observation->EnspOLF-1998                 5.3015.3015.3035.3045.3045.3015.3015.301
observation->Enspage-1999                 14.33214.33114.28714.27714.27714.33214.33214.331
observation->Enspage-2000                 13.97513.97313.96013.95413.95413.97513.97513.973
observation->Enspage-2001                 13.97913.95913.92913.92713.92713.97913.97913.959
observation->Enspage-2002                 12.08112.08712.07812.08512.08512.08112.08112.087
observation->Enspage-2003                 9.7009.7029.7069.7069.7069.7009.7009.702
observation->Enspage-2004                 12.96612.97212.98612.98912.98912.96612.96612.972
observation->Enspage-2005                 11.01211.00911.00911.00211.00211.01211.01211.009
observation->Enspage-2006                 12.74112.74412.71212.71112.71112.74112.74112.744
observation->Enspage-2007                 11.06111.06011.05211.05311.05311.06111.06111.060
observation->Enspage-2008                 12.10412.10012.10112.10112.10112.10412.10412.100
observation->Enspage-2009                 10.05610.05510.05510.05110.05110.05610.05610.055
observation->Enspage-2010                 17.58117.57617.62717.62517.62517.58117.58117.576
observation->Enspage-2011                 13.39913.40213.41213.42013.42013.39913.39913.402
observation->Enspage-2012                 13.14913.14813.13413.13913.13913.14913.14913.148
observation->Enspage-2013                 16.69416.69116.65916.65016.65016.69416.69416.691
observation->Enspage-2014                 13.86913.86813.87013.86213.86213.86913.86913.868
observation->Enspage-2015                 12.76012.76412.77612.78112.78112.76012.76012.764
observation->Enspage-2016                 19.22419.22219.20319.18919.18919.22419.22419.222
observation->Enspage-2017                 15.56215.55215.51115.49115.49115.56215.56215.552
observation->WnspOLF-1992                 10.12210.12410.12910.14310.14310.12210.12210.124
observation->WnspOLF-1993                 9.0459.0478.9918.9938.9939.0459.0459.047
observation->WnspOLF-1994                 15.93015.93115.89315.90615.90615.93015.93015.931
observation->WnspOLF-1996                 9.7889.7849.7529.7659.7659.7889.7889.784
observation->WnspOLF-1999                 11.55311.55311.59311.58311.58311.55311.55311.553
observation->WnspOLF-2000                 13.81213.81713.89213.88413.88413.81213.81213.817
observation->Wnspage-2001                 8.0328.0367.9947.9917.9918.0328.0328.036
observation->Wnspage-2002                 8.7158.7148.7018.6938.6938.7158.7158.714
observation->Wnspage-2003                 10.47310.47310.50710.49710.49710.47310.47310.473
observation->Wnspage-2004                 7.1557.1547.1407.1347.1347.1557.1557.154
observation->Wnspage-2006                 9.5899.5909.5519.5559.5559.5899.5899.590
observation->Wnspage-2007                 10.86110.86010.82210.82110.82110.86110.86110.860
observation->Wnspage-2008                 12.42512.42212.43512.43712.43712.42512.42512.422
observation->Wnspage-2009                 14.71614.71914.79014.78614.78614.71614.71614.719
observation->Wnspage-2010                 11.40511.40511.37011.36411.36411.40511.40511.405
observation->Wnspage-2011                 11.26711.26511.27511.27411.27411.26711.26711.265
observation->Wnspage-2012                 10.45410.45310.46510.46610.46610.45410.45410.453
observation->Wnspage-2013                 13.63313.63413.63413.63613.63613.63313.63313.634
observation->Wnspage-2014                 12.60812.60912.59712.59012.59012.60812.60812.609
observation->Wnspage-2016                 15.68715.68315.72215.71815.71815.68715.68715.683
observation->CRsumage-1992                 15.58415.57015.56615.55815.55815.58415.58415.570
observation->CRsumage-1993                 10.61610.61310.62410.62110.62110.61610.61610.613
observation->CRsumage-1994                 18.17018.17418.13018.12218.12218.17018.17018.174
observation->CRsumage-1995                 14.28514.28714.24214.23814.23814.28514.28514.287
observation->CRsumage-1996                 11.56711.56611.60711.62311.62311.56711.56711.566
observation->CRsumage-1997                 15.75415.75015.68815.67315.67315.75415.75415.750
observation->CRsumage-1998                 14.69014.68614.69014.69914.69914.69014.69014.686
observation->CRsumage-1999                 12.06112.06112.08412.09112.09112.06112.06112.061
observation->CRsumage-2000                 14.32314.32614.28314.28414.28414.32314.32314.326
observation->CRsumage-2001                 19.65919.65119.52019.51119.51119.65919.65919.651
observation->CRsumage-2002                 10.96910.97110.96010.96010.96010.96910.96910.971
observation->CRsumage-2003                 11.25111.25411.21011.20811.20811.25111.25111.254
observation->CRsumage-2004                 9.5539.5569.5619.5709.5709.5539.5539.556
observation->CRsumage-2005                 12.75312.74912.65412.64312.64312.75312.75312.749
observation->CRsumage-2006                 10.31610.31710.31710.31310.31310.31610.31610.317
observation->CRsumage-2007                 13.56213.56113.50413.49813.49813.56213.56213.561
observation->CRsumage-2008                 11.66111.66511.63911.63711.63711.66111.66111.665
observation->CRsumage-2009                 12.00612.00211.96511.96211.96212.00612.00612.002
observation->CRsumage-2010                 11.04811.05211.05511.05011.05011.04811.04811.052
observation->CRsumage-2011                 12.57912.57712.57112.56212.56212.57912.57912.577
observation->CRsumage-2012                 17.22817.23017.14117.14617.14617.22817.22817.230
observation->CRsumage-2013                 11.84311.84511.82211.81211.81211.84311.84311.845
observation->CRsumage-2014                 11.28611.28811.27111.26711.26711.28611.28611.288
observation->CRsumage-2016                 9.8669.8679.8479.8379.8379.8669.8669.867
observation->CRsumage-2018                 11.93111.93511.89511.88411.88411.93111.93111.935
observation->SAsumage-1992                 12.24612.24112.26912.24812.24812.24612.24612.241
observation->SAsumage-1993                 12.47012.48312.50212.47412.47412.47012.47012.483
observation->SAsumage-1994                 10.81110.80810.81810.80810.80810.81110.81110.808
observation->SAsumage-2001                 12.74912.76212.83912.80312.80312.74912.74912.762
observation->SAsumage-2002                 12.20912.21612.25412.21012.21012.20912.20912.216
observation->SAsumage-2003                 13.38613.38813.38613.32313.32313.38613.38613.388
observation->SAsumage-2004                 11.06711.06411.00510.98110.98111.06711.06711.064
observation->SAsumage-2005                 15.27815.28015.38615.46515.46515.27815.27815.280
observation->SAsumage-2006                 14.11214.11014.07814.11114.11114.11214.11214.110
observation->SAsumage-2007                 10.64910.64910.63910.59310.59310.64910.64910.649
observation->SAsumage-2008                 13.77113.76613.83613.92013.92013.77113.77113.766
observation->SAsumage-2009                 15.51315.52015.53015.56515.56515.51315.51315.520
observation->SAsumage-2010                 15.08115.08215.13015.20015.20015.08115.08115.082
observation->SAsumage-2012                 13.43713.43913.47913.46913.46913.43713.43713.439
observation->SAsumage-2013                 11.95411.95611.98211.97611.97611.95411.95411.956
observation->SAsumage-2015                 13.52213.52413.54013.55713.55713.52213.52213.524
observation->SAsumage-2017                 12.49212.48712.47812.47612.47612.49212.49212.487
observation->SAautage-1992                 11.80911.81911.85711.82911.82911.80911.80911.819
observation->SAautage-1996                 10.44910.45010.42610.45310.45310.44910.44910.450
observation->SAautage-1998                 12.80912.81012.83512.81112.81112.80912.80912.810
observation->pspawn_1993                 -6.017-6.016-6.015-6.021-6.021-6.017-6.017-6.016
observation->pspawn-1992                 -4.848-4.852-4.829-4.817-4.817-4.848-4.848-4.852
observation->pspawn-1998                 -8.284-8.291-8.300-8.306-8.306-8.284-8.284-8.291
prior->CSacousq->catchability[CSacous].q               -0.849-0.847-0.839-0.831-0.831-0.849-0.849-0.847
prior->WCacousq->catchability[WCacous].q               -1.162-1.163-1.202-1.212-1.212-1.162-1.162-1.163
prior->CRsumq->catchability[CRsum].q               -2.155-2.153-2.207-2.217-2.217-2.155-2.155-2.153
prior->SAsumq->catchability[SAsum].q               -1.762-1.760-1.557-1.450-1.450-1.762-1.762-1.760
prior->SAautq->catchability[SAaut].q               -1.913-1.911-1.762-1.677-1.677-1.913-1.913-1.911
prior->CR_process_error->observation[CRsumbio].process_error   0.0000.0000.0000.0000.0000.0000.0000.000
prior->SA_process_error->observation[SAsumbio].process_error   0.0000.0000.0000.0000.0000.0000.0000.000
prior->B0_E_with_total_log_b0_prior->process[recruit_E].b0              0.0000.0000.0000.0000.0000.0000.0000.000
prior->B0_W_with_proportion_prior->process[recruit_W].b0              12.54412.54512.55512.56212.56212.54412.54412.545
prior->M_all->process[Instant_mortality].m{west.sa}             -1.085-1.083-1.217-1.230-1.230-1.085-1.085-1.083
prior->Wspsl_shift_param->time_varying[shifted_mu].a               0.4200.4220.3780.3760.3760.4200.4200.422
prior->YCS_E->process[recruit_E].ycs_values{1975}-0.624-0.624-0.623-0.623-0.623-0.624-0.624-0.624
prior->YCS_E->process[recruit_E].ycs_values{1976}-0.316-0.314-0.319-0.323-0.323-0.316-0.316-0.314
prior->YCS_E->process[recruit_E].ycs_values{1977}-0.227-0.225-0.238-0.243-0.243-0.227-0.227-0.225
prior->YCS_E->process[recruit_E].ycs_values{1978}0.6530.6560.6150.6010.6010.6540.6540.656
prior->YCS_E->process[recruit_E].ycs_values{1979}0.0840.0860.0620.0530.0530.0840.0840.086
prior->YCS_E->process[recruit_E].ycs_values{1980}-0.630-0.630-0.627-0.625-0.625-0.630-0.630-0.630
prior->YCS_E->process[recruit_E].ycs_values{1981}-0.619-0.619-0.623-0.625-0.625-0.619-0.619-0.619
prior->YCS_E->process[recruit_E].ycs_values{1982}-0.550-0.551-0.542-0.539-0.539-0.550-0.550-0.551
prior->YCS_E->process[recruit_E].ycs_values{1983}-0.627-0.627-0.630-0.631-0.631-0.627-0.627-0.627
prior->YCS_E->process[recruit_E].ycs_values{1984}-0.591-0.591-0.596-0.597-0.597-0.591-0.591-0.591
prior->YCS_E->process[recruit_E].ycs_values{1985}-0.641-0.641-0.642-0.642-0.642-0.641-0.641-0.641
prior->YCS_E->process[recruit_E].ycs_values{1986}-0.408-0.408-0.400-0.398-0.398-0.408-0.408-0.408
prior->YCS_E->process[recruit_E].ycs_values{1987}0.1420.1420.1350.1320.1320.1420.1420.142
prior->YCS_E->process[recruit_E].ycs_values{1988}0.0260.0250.0190.0170.0170.0260.0260.025
prior->YCS_E->process[recruit_E].ycs_values{1989}-0.631-0.631-0.632-0.632-0.632-0.631-0.631-0.631
prior->YCS_E->process[recruit_E].ycs_values{1990}0.1590.1590.1580.1570.1570.1590.1590.159
prior->YCS_E->process[recruit_E].ycs_values{1991}-0.643-0.643-0.643-0.643-0.643-0.643-0.643-0.643
prior->YCS_E->process[recruit_E].ycs_values{1992}-0.643-0.643-0.643-0.642-0.642-0.643-0.643-0.643
prior->YCS_E->process[recruit_E].ycs_values{1993}-0.643-0.643-0.643-0.643-0.643-0.643-0.643-0.643
prior->YCS_E->process[recruit_E].ycs_values{1994}-0.530-0.531-0.525-0.523-0.523-0.530-0.530-0.531
prior->YCS_E->process[recruit_E].ycs_values{1995}-0.534-0.534-0.538-0.540-0.540-0.534-0.534-0.534
prior->YCS_E->process[recruit_E].ycs_values{1996}-0.574-0.573-0.577-0.578-0.578-0.574-0.574-0.573
prior->YCS_E->process[recruit_E].ycs_values{1997}-0.623-0.623-0.622-0.621-0.621-0.623-0.623-0.623
prior->YCS_E->process[recruit_E].ycs_values{1998}-0.512-0.511-0.513-0.514-0.514-0.512-0.512-0.511
prior->YCS_E->process[recruit_E].ycs_values{1999}2.0142.0142.0142.0142.0142.0142.0142.014
prior->YCS_E->process[recruit_E].ycs_values{2000}-0.616-0.616-0.614-0.614-0.614-0.616-0.616-0.616
prior->YCS_E->process[recruit_E].ycs_values{2001}-0.065-0.065-0.071-0.074-0.074-0.065-0.065-0.065
prior->YCS_E->process[recruit_E].ycs_values{2002}-0.543-0.542-0.545-0.545-0.545-0.543-0.543-0.542
prior->YCS_E->process[recruit_E].ycs_values{2003}-0.586-0.586-0.585-0.585-0.585-0.586-0.586-0.586
prior->YCS_E->process[recruit_E].ycs_values{2004}-0.568-0.568-0.568-0.568-0.568-0.568-0.568-0.568
prior->YCS_E->process[recruit_E].ycs_values{2005}-0.579-0.579-0.578-0.578-0.578-0.579-0.579-0.579
prior->YCS_E->process[recruit_E].ycs_values{2006}-0.483-0.483-0.482-0.482-0.482-0.483-0.483-0.483
prior->YCS_E->process[recruit_E].ycs_values{2007}-0.567-0.567-0.566-0.566-0.566-0.567-0.567-0.567
prior->YCS_E->process[recruit_E].ycs_values{2008}-0.643-0.643-0.643-0.643-0.643-0.643-0.643-0.643
prior->YCS_E->process[recruit_E].ycs_values{2009}-0.561-0.561-0.562-0.561-0.561-0.561-0.561-0.561
prior->YCS_E->process[recruit_E].ycs_values{2010}-0.031-0.031-0.046-0.050-0.050-0.031-0.031-0.031
prior->YCS_E->process[recruit_E].ycs_values{2011}-0.408-0.408-0.408-0.407-0.407-0.408-0.408-0.408
prior->YCS_E->process[recruit_E].ycs_values{2012}-0.019-0.019-0.023-0.025-0.025-0.019-0.019-0.019
prior->YCS_E->process[recruit_E].ycs_values{2013}-0.238-0.238-0.242-0.244-0.244-0.238-0.238-0.238
prior->YCS_E->process[recruit_E].ycs_values{2014}-0.317-0.317-0.314-0.312-0.312-0.317-0.317-0.317
prior->YCS_E->process[recruit_E].ycs_values{2015}-0.279-0.284-0.302-0.308-0.308-0.279-0.279-0.284
prior->YCS_E->process[recruit_E].ycs_values{2016}0.3630.3640.3730.3730.3730.3630.3630.364
prior->YCS_W->process[recruit_W].ycs_values{1975}-0.616-0.616-0.617-0.619-0.619-0.616-0.616-0.616
prior->YCS_W->process[recruit_W].ycs_values{1976}-0.195-0.195-0.184-0.162-0.162-0.195-0.195-0.195
prior->YCS_W->process[recruit_W].ycs_values{1977}-0.376-0.376-0.396-0.386-0.386-0.376-0.376-0.376
prior->YCS_W->process[recruit_W].ycs_values{1978}-0.396-0.397-0.417-0.419-0.419-0.396-0.396-0.397
prior->YCS_W->process[recruit_W].ycs_values{1979}-0.607-0.607-0.612-0.612-0.612-0.607-0.607-0.607
prior->YCS_W->process[recruit_W].ycs_values{1980}-0.567-0.568-0.573-0.573-0.573-0.567-0.567-0.568
prior->YCS_W->process[recruit_W].ycs_values{1981}-0.502-0.502-0.508-0.510-0.510-0.502-0.502-0.502
prior->YCS_W->process[recruit_W].ycs_values{1982}-0.606-0.606-0.607-0.607-0.607-0.606-0.606-0.606
prior->YCS_W->process[recruit_W].ycs_values{1983}-0.109-0.108-0.111-0.112-0.112-0.109-0.109-0.108
prior->YCS_W->process[recruit_W].ycs_values{1984}-0.163-0.161-0.163-0.166-0.166-0.163-0.163-0.161
prior->YCS_W->process[recruit_W].ycs_values{1985}-0.619-0.619-0.620-0.619-0.619-0.619-0.619-0.619
prior->YCS_W->process[recruit_W].ycs_values{1986}-0.098-0.097-0.098-0.099-0.099-0.098-0.098-0.097
prior->YCS_W->process[recruit_W].ycs_values{1987}0.7880.7890.7820.7850.7850.7880.7880.789
prior->YCS_W->process[recruit_W].ycs_values{1988}-0.252-0.251-0.255-0.252-0.252-0.252-0.252-0.251
prior->YCS_W->process[recruit_W].ycs_values{1989}1.2071.2071.2111.2101.2101.2071.2071.207
prior->YCS_W->process[recruit_W].ycs_values{1990}1.1971.1981.2041.2061.2061.1971.1971.198
prior->YCS_W->process[recruit_W].ycs_values{1991}-0.081-0.081-0.080-0.077-0.077-0.081-0.081-0.081
prior->YCS_W->process[recruit_W].ycs_values{1992}0.4800.4800.4800.4790.4790.4800.4800.480
prior->YCS_W->process[recruit_W].ycs_values{1993}-0.643-0.643-0.643-0.643-0.643-0.643-0.643-0.643
prior->YCS_W->process[recruit_W].ycs_values{1994}0.0140.0140.0200.0200.0200.0140.0140.014
prior->YCS_W->process[recruit_W].ycs_values{1995}-0.410-0.409-0.413-0.413-0.413-0.410-0.410-0.409
prior->YCS_W->process[recruit_W].ycs_values{1996}-0.301-0.301-0.306-0.305-0.305-0.301-0.301-0.301
prior->YCS_W->process[recruit_W].ycs_values{1997}-0.466-0.467-0.471-0.470-0.470-0.466-0.466-0.467
prior->YCS_W->process[recruit_W].ycs_values{1998}-0.322-0.323-0.334-0.335-0.335-0.322-0.322-0.323
prior->YCS_W->process[recruit_W].ycs_values{1999}2.0142.0142.0142.0142.0142.0142.0142.014
prior->YCS_W->process[recruit_W].ycs_values{2000}-0.643-0.643-0.643-0.643-0.643-0.643-0.643-0.643
prior->YCS_W->process[recruit_W].ycs_values{2001}0.8560.8550.8460.8460.8460.8560.8560.855
prior->YCS_W->process[recruit_W].ycs_values{2002}-0.222-0.222-0.222-0.223-0.223-0.222-0.222-0.222
prior->YCS_W->process[recruit_W].ycs_values{2003}-0.612-0.612-0.612-0.613-0.613-0.612-0.612-0.612
prior->YCS_W->process[recruit_W].ycs_values{2004}-0.570-0.570-0.571-0.572-0.572-0.570-0.570-0.570
prior->YCS_W->process[recruit_W].ycs_values{2005}-0.574-0.574-0.576-0.577-0.577-0.574-0.574-0.574
prior->YCS_W->process[recruit_W].ycs_values{2006}-0.280-0.280-0.279-0.280-0.280-0.280-0.280-0.280
prior->YCS_W->process[recruit_W].ycs_values{2007}-0.438-0.438-0.436-0.436-0.436-0.438-0.438-0.438
prior->YCS_W->process[recruit_W].ycs_values{2008}-0.464-0.464-0.463-0.463-0.463-0.464-0.464-0.464
prior->YCS_W->process[recruit_W].ycs_values{2009}-0.514-0.514-0.508-0.507-0.507-0.514-0.514-0.514
prior->YCS_W->process[recruit_W].ycs_values{2010}0.0710.0700.0780.0800.0800.0710.0710.070
prior->YCS_W->process[recruit_W].ycs_values{2011}0.0310.0300.0430.0440.0440.0310.0310.030
prior->YCS_W->process[recruit_W].ycs_values{2012}-0.050-0.049-0.059-0.060-0.060-0.050-0.050-0.049
prior->YCS_W->process[recruit_W].ycs_values{2013}-0.489-0.488-0.490-0.490-0.490-0.489-0.489-0.488
prior->YCS_W->process[recruit_W].ycs_values{2014}1.7301.7271.7421.7451.7451.7301.7301.727
prior->YCS_W->process[recruit_W].ycs_values{2015}1.6811.6841.6871.6891.6891.6811.6811.684
prior->YCS_W->process[recruit_W].ycs_values{2016}0.3630.3640.3730.3730.3730.3630.3630.364
prior->sel_Whome->selectivity[sel_Whome].v{1}            0.0000.0000.0000.0000.0000.0000.0000.000
prior->sel_Whome->selectivity[sel_Whome].v{2}            0.0000.0000.0000.0000.0000.0000.0000.000
prior->sel_Whome->selectivity[sel_Whome].v{3}            0.0000.0000.0000.0000.0000.0000.0000.000
prior->sel_Whome->selectivity[sel_Whome].v{4}            0.0000.0000.0000.0000.0000.0000.0000.000
prior->sel_Whome->selectivity[sel_Whome].v{5}            0.0000.0000.0000.0000.0000.0000.0000.000
prior->sel_Whome->selectivity[sel_Whome].v{6}            0.0000.0000.0000.0000.0000.0000.0000.000
prior->sel_Whome->selectivity[sel_Whome].v{7}            0.0000.0000.0000.0000.0000.0000.0000.000
prior->sel_Espmg_male->selectivity[sel_Espmg].v{1}            0.0000.0000.0000.0000.0000.0000.0000.000
prior->sel_Espmg_male->selectivity[sel_Espmg].v{2}            0.0000.0000.0000.0000.0000.0000.0000.000
prior->sel_Espmg_male->selectivity[sel_Espmg].v{3}            0.0000.0000.0000.0000.0000.0000.0000.000
prior->sel_Espmg_male->selectivity[sel_Espmg].v{4}            0.0000.0000.0000.0000.0000.0000.0000.000
prior->sel_Espmg_male->selectivity[sel_Espmg].v{5}            0.0000.0000.0000.0000.0000.0000.0000.000
prior->sel_Espmg_male->selectivity[sel_Espmg].v{6}            0.0000.0000.0000.0000.0000.0000.0000.000
prior->sel_Espmg_male->selectivity[sel_Espmg].v{7}            0.0000.0000.0000.0000.0000.0000.0000.000
prior->sel_Espmg_male->selectivity[sel_Espmg].v{8}            0.0000.0000.0000.0000.0000.0000.0000.000
prior->sel_Wspmg_male->selectivity[sel_Wspmg].v{1}            0.0000.0000.0000.0000.0000.0000.0000.000
prior->sel_Wspmg_male->selectivity[sel_Wspmg].v{2}            0.0000.0000.0000.0000.0000.0000.0000.000
prior->sel_Wspmg_male->selectivity[sel_Wspmg].v{3}            0.0000.0000.0000.0000.0000.0000.0000.000
prior->sel_Wspmg_male->selectivity[sel_Wspmg].v{4}            0.0000.0000.0000.0000.0000.0000.0000.000
prior->sel_Wspmg_male->selectivity[sel_Wspmg].v{5}            0.0000.0000.0000.0000.0000.0000.0000.000
prior->sel_Wspmg_male->selectivity[sel_Wspmg].v{6}            0.0000.0000.0000.0000.0000.0000.0000.000
prior->sel_Wspmg_male->selectivity[sel_Wspmg].v{7}            0.0000.0000.0000.0000.0000.0000.0000.000
prior->sel_Wspmg_male->selectivity[sel_Wspmg].v{8}            0.0000.0000.0000.0000.0000.0000.0000.000
prior->Enspsl_mu->selectivity[Enspsl].mu              0.0000.0000.0000.0000.0000.0000.0000.000
prior->Enspsl_s_l->selectivity[Enspsl].sigma_l         0.0000.0000.0000.0000.0000.0000.0000.000
prior->Enspsl_s_r->selectivity[Enspsl].sigma_r         0.0000.0000.0000.0000.0000.0000.0000.000
prior->Wnspsl_mu->selectivity[Wnspsl].mu              0.0000.0000.0000.0000.0000.0000.0000.000
prior->Wnspsl_s_l->selectivity[Wnspsl].sigma_l         0.0000.0000.0000.0000.0000.0000.0000.000
prior->Wnspsl_s_r->selectivity[Wnspsl].sigma_r         0.0000.0000.0000.0000.0000.0000.0000.000
prior->Espsl_mu->selectivity[Espsl].mu              0.0000.0000.0000.0000.0000.0000.0000.000
prior->Espsl_s_l->selectivity[Espsl].sigma_l         0.0000.0000.0000.0000.0000.0000.0000.000
prior->Espsl_s_r->selectivity[Espsl].sigma_r         0.0000.0000.0000.0000.0000.0000.0000.000
prior->CRsl_mu->selectivity[CRsl].mu              0.0000.0000.0000.0000.0000.0000.0000.000
prior->CRsl_s_l->selectivity[CRsl].sigma_l         0.0000.0000.0000.0000.0000.0000.0000.000
prior->CRsl_s_r->selectivity[CRsl].sigma_r         0.0000.0000.0000.0000.0000.0000.0000.000
prior->SAsl_mu->selectivity[SAsl].mu              0.0000.0000.0000.0000.0000.0000.0000.000
prior->SAsl_s_l->selectivity[SAsl].sigma_l         0.0000.0000.0000.0000.0000.0000.0000.000
prior->SAsl_s_r->selectivity[SAsl].sigma_r         0.0000.0000.0000.0000.0000.0000.0000.000
additional_prior->YCS.eq.16              0.0000.0000.0000.0000.0000.0000.0000.000
additional_prior->sp.migr            0.0090.0090.0130.0150.0150.0090.0090.009
jacobian->log_sum_b0                 0.0000.0000.0000.0000.0000.0000.0000.000
total_negloglike                 1946.8101946.8001946.5401946.5501946.5501946.8101946.8101946.800

## [1] "CASAL base model convergence information"
## [1] "fmm: have converged: t = 8.24015e-007 f = 1946.54"                                                        
## [2] "Successful convergence in optimise"                                                                       
## [3] "Minimiser achieved convergence after 599 quasi-Newton iterations using 669 objective function evaluations"
## [1] ""
## [1] "CASAL sensitivity 1 model convergence information"
## [1] "fmm: step size too small. Indicates successful convergence (though this is not the textbook ideal convergence situation)"
## [2] "Successful convergence in optimise"                                                                                      
## [3] "Minimiser achieved convergence after 665 quasi-Newton iterations using 765 objective function evaluations"               
## [1] ""
## [1] "Casal2 betadiff_casal_flags_on model convergence information"
## [1] "fmm: have converged: t = 9.26886e-07 f = 1946.81"
## [2] "Successful convergence in optimise"              
## [1] ""
## [1] "Casal2 betadiff_casal_flags_off model convergence information"
## [1] "fmm: have converged: t = 1.51392e-07 f = 1946.8"
## [2] "Successful convergence in optimise"             
## [1] ""
## [1] "Casal2 betadiff_casal_flags_on_low_tol model convergence information"
## [1] "fmm: step size too small. Indicates successful convergence (though this is not the textbook ideal convergence situation)"
## [2] "Successful convergence in optimise"                                                                                      
## [1] ""
## [1] "Casal2 cppad_casal_flags_on model convergence information"
##  [1] "Number of nonzeros in equality constraint Jacobian...:        0"
##  [2] "Number of nonzeros in inequality constraint Jacobian.:      133"
##  [3] "Number of nonzeros in Lagrangian Hessian.............:     8911"
##  [4] "Number of Iterations....: 72"                                   
##  [5] "Number of objective function evaluations             = 109"     
##  [6] "Number of objective gradient evaluations             = 73"      
##  [7] "Number of equality constraint evaluations            = 0"       
##  [8] "Number of inequality constraint evaluations          = 109"     
##  [9] "Number of equality constraint Jacobian evaluations   = 0"       
## [10] "Number of inequality constraint Jacobian evaluations = 73"      
## [11] "Number of Lagrangian Hessian evaluations             = 72"      
## [12] "EXIT: Optimal Solution Found."                                  
## [13] "Number of nonzeros in equality constraint Jacobian...:        0"
## [14] "Number of nonzeros in inequality constraint Jacobian.:      133"
## [15] "Number of nonzeros in Lagrangian Hessian.............:     8911"
## [16] "Number of Iterations....: 16"                                   
## [17] "Number of objective function evaluations             = 22"      
## [18] "Number of objective gradient evaluations             = 17"      
## [19] "Number of equality constraint evaluations            = 0"       
## [20] "Number of inequality constraint evaluations          = 22"      
## [21] "Number of equality constraint Jacobian evaluations   = 0"       
## [22] "Number of inequality constraint Jacobian evaluations = 17"      
## [23] "Number of Lagrangian Hessian evaluations             = 16"      
## [24] "EXIT: Optimal Solution Found."                                  
## [1] ""
## [1] "Casal2 cppad_casal_flags_off model convergence information"
##  [1] "Number of nonzeros in equality constraint Jacobian...:        0"
##  [2] "Number of nonzeros in inequality constraint Jacobian.:      133"
##  [3] "Number of nonzeros in Lagrangian Hessian.............:     8911"
##  [4] "Number of Iterations....: 72"                                   
##  [5] "Number of objective function evaluations             = 109"     
##  [6] "Number of objective gradient evaluations             = 73"      
##  [7] "Number of equality constraint evaluations            = 0"       
##  [8] "Number of inequality constraint evaluations          = 109"     
##  [9] "Number of equality constraint Jacobian evaluations   = 0"       
## [10] "Number of inequality constraint Jacobian evaluations = 73"      
## [11] "Number of Lagrangian Hessian evaluations             = 72"      
## [12] "EXIT: Optimal Solution Found."                                  
## [13] "Number of nonzeros in equality constraint Jacobian...:        0"
## [14] "Number of nonzeros in inequality constraint Jacobian.:      133"
## [15] "Number of nonzeros in Lagrangian Hessian.............:     8911"
## [16] "Number of Iterations....: 16"                                   
## [17] "Number of objective function evaluations             = 22"      
## [18] "Number of objective gradient evaluations             = 17"      
## [19] "Number of equality constraint evaluations            = 0"       
## [20] "Number of inequality constraint evaluations          = 22"      
## [21] "Number of equality constraint Jacobian evaluations   = 0"       
## [22] "Number of inequality constraint Jacobian evaluations = 17"      
## [23] "Number of Lagrangian Hessian evaluations             = 16"      
## [24] "EXIT: Optimal Solution Found."                                  
## [1] ""
## [1] "Casal2 adolc_casal_flags_on model convergence information"
## character(0)
## [1] ""
## [1] "Casal2 adolc_casal_flags_off model convergence information"
## character(0)
## [1] ""
## [1] "Casal2 adolc_casal_flags_on_low_tol model convergence information"
## character(0)
## [1] "CASAL model warnings"
##                  parameter estimate lower.bound upper.bound
## 1   recruitment[E].YCS[25]     0.06        0.06         8.6
## 2   recruitment[W].YCS[25]     0.06        0.06         8.6
## 3 selectivity[CRsl].all[1]        1           1          17
## 4 selectivity[CRsl].all[2]        1           1          50
## [1] ""
## [1] "CASAL sensitivity 1 model warnings"
##                  parameter estimate lower.bound upper.bound
## 1   recruitment[E].YCS[25]     0.06        0.06         8.6
## 2   recruitment[W].YCS[25]     0.06        0.06         8.6
## 3 selectivity[CRsl].all[1]        1           1          17
## 4 selectivity[CRsl].all[2]        1           1          50
## [1] ""
## [1] "Casal2 betadiff_casal_flags_on model warnings"
## $warnings_found
## [1] 10
## 
## $warning_0
## [1] "Estimates were removed because of matching lower and upper bounds. Originally had 134 estimates, now have 133"
## 
## $warning_1
## [1] "estimated parameter 'process[recruit_E].b0' was within 0.001 of upper bound 16.2"
## 
## $warning_2
## [1] "estimated parameter 'process[recruit_W].b0' was within 0.001 of upper bound 0.59"
## 
## $warning_3
## [1] "estimated parameter 'process[recruit_E].ycs_values{1999}' was within 0.001 of lower bound 0.06"
## 
## $warning_4
## [1] "estimated parameter 'process[recruit_W].ycs_values{1999}' was within 0.001 of lower bound 0.06"
## 
## $warning_5
## [1] "estimated parameter 'selectivity[sel_Whome].v{7}' was within 0.001 of upper bound 1"
## 
## $warning_6
## [1] "estimated parameter 'selectivity[Enspsl].sigma_r' was within 0.001 of upper bound 50"
## 
## $warning_7
## [1] "estimated parameter 'selectivity[Wnspsl].sigma_r' was within 0.001 of upper bound 50"
## 
## $warning_8
## [1] "estimated parameter 'selectivity[CRsl].mu' was within 0.001 of lower bound 1"
## 
## $warning_9
## [1] "estimated parameter 'selectivity[SAsl].sigma_r' was within 0.001 of lower bound 1"
## 
## $type
## [1] "warnings"
## 
## [1] ""
## [1] "Casal2 betadiff_casal_flags_off model warnings"
## $warnings_found
## [1] 9
## 
## $warning_0
## [1] "Estimates were removed because of matching lower and upper bounds. Originally had 134 estimates, now have 133"
## 
## $warning_1
## [1] "estimated parameter 'process[recruit_E].b0' was within 0.001 of upper bound 16.2"
## 
## $warning_2
## [1] "estimated parameter 'process[recruit_W].b0' was within 0.001 of upper bound 0.59"
## 
## $warning_3
## [1] "estimated parameter 'process[recruit_E].ycs_values{1999}' was within 0.001 of lower bound 0.06"
## 
## $warning_4
## [1] "estimated parameter 'process[recruit_W].ycs_values{1999}' was within 0.001 of lower bound 0.06"
## 
## $warning_5
## [1] "estimated parameter 'selectivity[Enspsl].sigma_r' was within 0.001 of upper bound 50"
## 
## $warning_6
## [1] "estimated parameter 'selectivity[Wnspsl].sigma_r' was within 0.001 of upper bound 50"
## 
## $warning_7
## [1] "estimated parameter 'selectivity[CRsl].mu' was within 0.001 of lower bound 1"
## 
## $warning_8
## [1] "estimated parameter 'selectivity[SAsl].sigma_r' was within 0.001 of lower bound 1"
## 
## $type
## [1] "warnings"
## 
## [1] ""
## [1] "Casal2 betadiff_casal_flags_on_low_tol model warnings"
## $warnings_found
## [1] 6
## 
## $warning_0
## [1] "Estimates were removed because of matching lower and upper bounds. Originally had 134 estimates, now have 133"
## 
## $warning_1
## [1] "estimated parameter 'process[recruit_E].b0' was within 0.001 of upper bound 16.2"
## 
## $warning_2
## [1] "estimated parameter 'process[recruit_W].b0' was within 0.001 of upper bound 0.59"
## 
## $warning_3
## [1] "estimated parameter 'process[recruit_E].ycs_values{1999}' was within 0.001 of lower bound 0.06"
## 
## $warning_4
## [1] "estimated parameter 'process[recruit_W].ycs_values{1999}' was within 0.001 of lower bound 0.06"
## 
## $warning_5
## [1] "estimated parameter 'selectivity[CRsl].mu' was within 0.001 of lower bound 1"
## 
## $type
## [1] "warnings"
## 
## [1] ""
## [1] "Casal2 cppad_casal_flags_on model warnings"
## $warnings_found
## [1] 6
## 
## $warning_0
## [1] "Estimates were removed because of matching lower and upper bounds. Originally had 134 estimates, now have 133"
## 
## $warning_1
## [1] "estimated parameter 'process[recruit_E].b0' was within 0.001 of upper bound 16.2"
## 
## $warning_2
## [1] "estimated parameter 'process[recruit_W].b0' was within 0.001 of upper bound 0.59"
## 
## $warning_3
## [1] "estimated parameter 'process[recruit_E].ycs_values{1999}' was within 0.001 of lower bound 0.06"
## 
## $warning_4
## [1] "estimated parameter 'process[recruit_W].ycs_values{1999}' was within 0.001 of lower bound 0.06"
## 
## $warning_5
## [1] "estimated parameter 'selectivity[CRsl].mu' was within 0.001 of lower bound 1"
## 
## $type
## [1] "warnings"
## 
## [1] ""
## [1] "Casal2 cppad_casal_flags_off model warnings"
## $warnings_found
## [1] 6
## 
## $warning_0
## [1] "Estimates were removed because of matching lower and upper bounds. Originally had 134 estimates, now have 133"
## 
## $warning_1
## [1] "estimated parameter 'process[recruit_E].b0' was within 0.001 of upper bound 16.2"
## 
## $warning_2
## [1] "estimated parameter 'process[recruit_W].b0' was within 0.001 of upper bound 0.59"
## 
## $warning_3
## [1] "estimated parameter 'process[recruit_E].ycs_values{1999}' was within 0.001 of lower bound 0.06"
## 
## $warning_4
## [1] "estimated parameter 'process[recruit_W].ycs_values{1999}' was within 0.001 of lower bound 0.06"
## 
## $warning_5
## [1] "estimated parameter 'selectivity[CRsl].mu' was within 0.001 of lower bound 1"
## 
## $type
## [1] "warnings"
## 
## [1] ""
## [1] "Casal2 adolc_casal_flags_on model warnings"
## $warnings_found
## [1] 10
## 
## $warning_0
## [1] "Estimates were removed because of matching lower and upper bounds. Originally had 134 estimates, now have 133"
## 
## $warning_1
## [1] "estimated parameter 'process[recruit_E].b0' was within 0.001 of upper bound 16.2"
## 
## $warning_2
## [1] "estimated parameter 'process[recruit_W].b0' was within 0.001 of upper bound 0.59"
## 
## $warning_3
## [1] "estimated parameter 'process[recruit_E].ycs_values{1999}' was within 0.001 of lower bound 0.06"
## 
## $warning_4
## [1] "estimated parameter 'process[recruit_W].ycs_values{1999}' was within 0.001 of lower bound 0.06"
## 
## $warning_5
## [1] "estimated parameter 'selectivity[sel_Whome].v{7}' was within 0.001 of upper bound 1"
## 
## $warning_6
## [1] "estimated parameter 'selectivity[Enspsl].sigma_r' was within 0.001 of upper bound 50"
## 
## $warning_7
## [1] "estimated parameter 'selectivity[Wnspsl].sigma_r' was within 0.001 of upper bound 50"
## 
## $warning_8
## [1] "estimated parameter 'selectivity[CRsl].mu' was within 0.001 of lower bound 1"
## 
## $warning_9
## [1] "estimated parameter 'selectivity[SAsl].sigma_r' was within 0.001 of lower bound 1"
## 
## $type
## [1] "warnings"
## 
## [1] ""
## [1] "Casal2 adolc_casal_flags_off model warnings"
## $warnings_found
## [1] 10
## 
## $warning_0
## [1] "Estimates were removed because of matching lower and upper bounds. Originally had 134 estimates, now have 133"
## 
## $warning_1
## [1] "estimated parameter 'process[recruit_E].b0' was within 0.001 of upper bound 16.2"
## 
## $warning_2
## [1] "estimated parameter 'process[recruit_W].b0' was within 0.001 of upper bound 0.59"
## 
## $warning_3
## [1] "estimated parameter 'process[recruit_E].ycs_values{1999}' was within 0.001 of lower bound 0.06"
## 
## $warning_4
## [1] "estimated parameter 'process[recruit_W].ycs_values{1999}' was within 0.001 of lower bound 0.06"
## 
## $warning_5
## [1] "estimated parameter 'selectivity[sel_Whome].v{7}' was within 0.001 of upper bound 1"
## 
## $warning_6
## [1] "estimated parameter 'selectivity[Enspsl].sigma_r' was within 0.001 of upper bound 50"
## 
## $warning_7
## [1] "estimated parameter 'selectivity[Wnspsl].sigma_r' was within 0.001 of upper bound 50"
## 
## $warning_8
## [1] "estimated parameter 'selectivity[CRsl].mu' was within 0.001 of lower bound 1"
## 
## $warning_9
## [1] "estimated parameter 'selectivity[SAsl].sigma_r' was within 0.001 of lower bound 1"
## 
## $type
## [1] "warnings"
## 
## [1] ""
## [1] "Casal2 adolc_casal_flags_on_low_tol model warnings"
## $warnings_found
## [1] 9
## 
## $warning_0
## [1] "Estimates were removed because of matching lower and upper bounds. Originally had 134 estimates, now have 133"
## 
## $warning_1
## [1] "estimated parameter 'process[recruit_E].b0' was within 0.001 of upper bound 16.2"
## 
## $warning_2
## [1] "estimated parameter 'process[recruit_W].b0' was within 0.001 of upper bound 0.59"
## 
## $warning_3
## [1] "estimated parameter 'process[recruit_E].ycs_values{1999}' was within 0.001 of lower bound 0.06"
## 
## $warning_4
## [1] "estimated parameter 'process[recruit_W].ycs_values{1999}' was within 0.001 of lower bound 0.06"
## 
## $warning_5
## [1] "estimated parameter 'selectivity[Enspsl].sigma_r' was within 0.001 of upper bound 50"
## 
## $warning_6
## [1] "estimated parameter 'selectivity[Wnspsl].sigma_r' was within 0.001 of upper bound 50"
## 
## $warning_7
## [1] "estimated parameter 'selectivity[CRsl].mu' was within 0.001 of lower bound 1"
## 
## $warning_8
## [1] "estimated parameter 'selectivity[SAsl].sigma_r' was within 0.001 of lower bound 1"
## 
## $type
## [1] "warnings"

1.5 Matching of outputs

Time series comparisons with CASAL base model results

## [1] "Catch time series base model comparison for run betadiff_casal_flags_on"
## [1] "Actual catches for Ensp1 match: yes"
## [1] "Actual catches for Wnsp1 match: yes"
## [1] "Actual catches for Ensp2 match: yes"
## [1] "Actual catches for Wnsp2 match: yes"
## [1] "Actual catches for Esp match: yes"
## [1] "Actual catches for Wsp match: yes"
## [1] ""
## [1] "Catch time series base model comparison for run betadiff_casal_flags_off"
## [1] "Actual catches for Ensp1 match: yes"
## [1] "Actual catches for Wnsp1 match: yes"
## [1] "Actual catches for Ensp2 match: yes"
## [1] "Actual catches for Wnsp2 match: yes"
## [1] "Actual catches for Esp match: yes"
## [1] "Actual catches for Wsp match: yes"
## [1] ""
## [1] "Catch time series base model comparison for run betadiff_casal_flags_on_low_tol"
## [1] "Actual catches for Ensp1 match: yes"
## [1] "Actual catches for Wnsp1 match: yes"
## [1] "Actual catches for Ensp2 match: yes"
## [1] "Actual catches for Wnsp2 match: yes"
## [1] "Actual catches for Esp match: yes"
## [1] "Actual catches for Wsp match: yes"
## [1] ""
## [1] "Catch time series base model comparison for run cppad_casal_flags_on"
## [1] "Actual catches for Ensp1 match: yes"
## [1] "Actual catches for Wnsp1 match: yes"
## [1] "Actual catches for Ensp2 match: yes"
## [1] "Actual catches for Wnsp2 match: yes"
## [1] "Actual catches for Esp match: yes"
## [1] "Actual catches for Wsp match: yes"
## [1] ""
## [1] "Catch time series base model comparison for run cppad_casal_flags_off"
## [1] "Actual catches for Ensp1 match: yes"
## [1] "Actual catches for Wnsp1 match: yes"
## [1] "Actual catches for Ensp2 match: yes"
## [1] "Actual catches for Wnsp2 match: yes"
## [1] "Actual catches for Esp match: yes"
## [1] "Actual catches for Wsp match: yes"
## [1] ""
## [1] "Catch time series base model comparison for run adolc_casal_flags_on"
## [1] "Actual catches for Ensp1 match: yes"
## [1] "Actual catches for Wnsp1 match: yes"
## [1] "Actual catches for Ensp2 match: yes"
## [1] "Actual catches for Wnsp2 match: yes"
## [1] "Actual catches for Esp match: yes"
## [1] "Actual catches for Wsp match: yes"
## [1] ""
## [1] "Catch time series base model comparison for run adolc_casal_flags_off"
## [1] "Actual catches for Ensp1 match: yes"
## [1] "Actual catches for Wnsp1 match: yes"
## [1] "Actual catches for Ensp2 match: yes"
## [1] "Actual catches for Wnsp2 match: yes"
## [1] "Actual catches for Esp match: yes"
## [1] "Actual catches for Wsp match: yes"
## [1] ""
## [1] "Catch time series base model comparison for run adolc_casal_flags_on_low_tol"
## [1] "Actual catches for Ensp1 match: yes"
## [1] "Actual catches for Wnsp1 match: yes"
## [1] "Actual catches for Ensp2 match: yes"
## [1] "Actual catches for Wnsp2 match: yes"
## [1] "Actual catches for Esp match: yes"
## [1] "Actual catches for Wsp match: yes"
## [1] ""

Derived quantities

SB0, SBcurrent, MSY, F_MSY, others…

1.6 Plots

Comparison plots

## [1] "CASAL base parameter correlation range (excluding 1.0): -0.9914 0.9969"

## [1] "CASAL sensitivity 1 parameter correlation range (excluding 1.0): -0.9324 0.9968"

## [1] "Casal2 betadiff_casal_flags_on parameter correlation range (excluding 1.0): -0.883725062900015 0.996652309886526"
## Warning in min(x): no non-missing arguments to min; returning Inf
## Warning in max(x): no non-missing arguments to max; returning -Inf

## [1] "Casal2 betadiff_casal_flags_off parameter correlation range (excluding 1.0): Inf -Inf"

## [1] "Casal2 betadiff_casal_flags_on_low_tol parameter correlation range (excluding 1.0): -0.928324892874476 0.996774805428128"

## [1] "Casal2 cppad_casal_flags_on parameter correlation range (excluding 1.0): -0.950676943786571 0.99752098518567"

## [1] "Casal2 cppad_casal_flags_off parameter correlation range (excluding 1.0): -0.950676943786571 0.99752098518567"

## [1] "Casal2 adolc_casal_flags_on parameter correlation range (excluding 1.0): -0.883292041222854 0.996669052726936"

## [1] "Casal2 adolc_casal_flags_off parameter correlation range (excluding 1.0): -0.879486504060093 0.996659497184991"

## [1] "Casal2 adolc_casal_flags_on_low_tol parameter correlation range (excluding 1.0): -0.955631418458889 0.996683532981232"